39 2. Geophysical Assessment a. Geologic mapping Field geologic mapping was conducted in the Angat Dam watershed as part of the project‟s activities. The following briefly describe the group‟s observations. The Angat watershed is underlain by Late Eocene to Early Oligocene igneous and sedimentary rocks that comprise the Bayabas Formation (Peña, 2008 and references cited therein) (Fig. IV- 24). Geologic field data obtained from the watershed show that the interbedded sandstones and siltstones are overlain by andesites. East of the spillway at Sitio Dike, minor exposures of interbedded sandstones and siltstones were observed (Fig. IV-25). Outcrop samples are generally dark in color and sometimes silicified. Thickness of beds range from 1 to 40 cm, with laminations of siltstones also observed between sandstone beds. Sandstones exhibit very fine- to medium-grained textures, and are often arkosic with a few oxidized volcanic fragments. Siltstones, on the other hand, exhibit thinner (1 to 3 cm) and more friable beds compared to the more indurated sandstones. In some exposures, they are light gray in color and tuffaceous.
Transcript
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2. Geophysical Assessment a. Geologic mapping
Field geologic mapping was conducted in the Angat Dam watershed as part of the project‟s activities. The following briefly describe the group‟s observations. The Angat watershed is underlain by Late Eocene to Early Oligocene igneous and sedimentary rocks that comprise the Bayabas Formation (Peña, 2008 and references cited therein) (Fig. IV-24). Geologic field data obtained from the watershed show that the interbedded sandstones and siltstones are overlain by andesites. East of the spillway at Sitio Dike, minor exposures of interbedded sandstones and siltstones were observed (Fig. IV-25). Outcrop samples are generally dark in color and sometimes silicified. Thickness of beds range from 1 to 40 cm, with laminations of siltstones also observed between sandstone beds. Sandstones exhibit very fine- to medium-grained textures, and are often arkosic with a few oxidized volcanic fragments. Siltstones, on the other hand, exhibit thinner (1 to 3 cm) and more friable beds compared to the more indurated sandstones. In some exposures, they are light gray in color and tuffaceous.
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Figure IV-24. Map shows the topographic and geologic characteristics of the Angat watershed. The area is generally underlain by andesites with minor exposures of interbedded sandstones and siltstones. Topography data are from ERSDAC, 2011, while lineaments are adapted from the Angat HEPP Technical Report.
Figure IV-25. Minor exposure of interbedded sandstones and siltstones at Sitio Dike, east of the spillway (Coordinates: N14°54.330‟ E121°10.802‟ WGS84). Beds strike northwest and dip towards the southwest (Fig. III-24, map).
Overlying the interbedded sandstones and siltstones are andesites that exhibit aphanitic, porphyritic, and agglomeratic characteristics. Field observations suggest that the andesites were emplaced as flows. When coarse-grained, bloated feldspars are evident while pyroxene and amphibole phenocrysts are also commonly observed. In most outcrops, andesites appear highly weathered, densely fractured, and sheared, sometimes exhibiting striated surfaces or slickensides (Fig. IV-26a and b). Joint sets generally strike NW and NE, and dip towards the NE and NW, respectively.
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Figure IV-26a. Exposure of highly sheared andesites observed west of the spillway (Coordinates: N14°54.420‟ E121°09.967‟ WGS84). Note the „scratches‟ (striations/slickenlines) parallel to the pen. Pen is approximately 10 cm-long (Figure III-26b).
b. Geohazards assessment
Geohazards are dangers present in an area that may be triggered by various natural or anthropogenic activities such as earthquakes, ground shaking, volcanic eruptions, heavy rainfall or man-induced earth movement. The likelihood for these hazards to manifest is also controlled by the underlying geology of an area. The Philippine archipelago is a tectonically active region frequently affected by numerous crustal movements at varying depths and magnitudes. Geohazards relevant to the study area will be discussed in the following sections. Fault-related/seismic hazards
The Philippine archipelago is a tectonically active region frequently affected by numerous crustal movements at varying depths and magnitudes. Figure 6 plots the epicenters of earthquake occurrences in the Philippines from 1973 to 2012 (NEIC-USGS, 2012). Earthquake data for the Angat area show that this region experiences relatively fewer earthquakes than the rest of the archipelago. Furthermore, the area has lesser moderate to deep hypocenters as compared with other parts of the Philippines. The few epicenters close to the northern trace of the WVF are mostly of ~M4.2 to M4.8 and these originated from <35 km depths (Fig. IV-27). Ground acceleration
Seismic waves travelling from the earthquake source (focus) to the surface cause vibrations or trembling. The degree of damage associated with ground tremors is attributed to several factors including: wavelength and duration of shaking, the distance from the epicenter, the nature of the underlying materials, the degree of water saturation of soil/rock media, and the character of infrastructures within the area (Johnson and DeGraff, 1988). From worldwide post-quake studies of large-magnitude earthquake events, earthquake intensity is notably less in areas underlain by bedrock compared to those underlain by soft foundation materials (e.g. sand and clay) (Daligdig&Besana, 1993). Other factors such as the degree of weathering and the presence of structures (fractures, joints, beddings, faults) may further increase the effects of ground motion. Field surveys need to be conducted to assess the type of materials that underlie the study area/s.
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Figure IV-27. Earthquake epicenters collated from 1973 to 2012 illustrates the number, depth and magnitude of the various events near the study area. Map was drawn using data from the NEIC-USGS (2012). The color scale on the left depicts the depth of the earthquake source (in kilometres).
To quantitatively describe the effects of ground movements, the Peak Ground Acceleration (PGA) is used to calculate the maximum acceleration expected to be experienced by ground particles during an earthquake. It gives an idea as to how hard the earth shakes at a given geographic location, taking into consideration the strength of the quake, distance from the source and type of rocks/soil in the area. It is expressed in terms of “g” or “%g”. Values of g close to 0.3 or % g ≈ 30 are usually taken to suggest significant effect or damage to man-made structures. Calculations for the Angat Dam site were done using the attenuation relationship equation of Fukushima and Tanaka (1990) using assumed or best approximate values of magnitude and distance (Table IV-1). This attenuation relationship equation is stated as: Log 10 A = 0.41M – log 10 (R + 0.032 x 10 0.4 M) – 0.0034 R + 1.30, (Equation 1) Where: A is the peak acceleration, R is the shortest distance between the site and the earthquake generator, and M is the considered probable magnitude to be produced by the earthquake generator. Correction factors (0.6 for rock, 0.87 for medium soil, and 1.39 for soft soil) are incorporated based on the nature of the underlying materials at the project site. Computations done used different possible earthquake generators, earthquake strengths and type of underlying materials (rock, medium soil and soft soil). The best proxy for the ground characteristics of the communities near Angat may range between the Medium Soil and Soft Soil characteristics.
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Magnitudes 3, 5 and 7 were used in the calculations to give a representative set of PGA values for different possible earthquake scenarios. Table IV-1. Peak ground acceleration resulting from various earthquake generators is computed using the attenuation equation of Fukushima and Tanaka (1990).
Values from Table IV-1 clearly show that the Manila Trench and the Philippine Fault
Zone have minor influence on the ground acceleration of the Angat area for magnitudes lower than 7. Earthquake generators that may have significant effects on the area especially on large engineering structures such as Angat Dam include the West and East Valley Faults. Of particular concern is the West Valley Fault whose trace is less than 1 km away from the main Angat Dam dike. Significant ground acceleration can lead to ruptures, produce liquefaction, subsidence, differential settlement and various other hazards. Mass movement/Landslides The term "landslide" describes a wide variety of processes that result in the downward and outward movement of slope-forming materials including rock, soil, artificial fill, or a combination of these. The materials may move by falling, toppling, sliding, spreading, or flowing. Table IV-2 summarizes the commonly accepted terminologies for mass movements. Table IV-2. Types of mass movements, modified from Varnes' classification of slope movements.
Type Of Movement Type Of Material Bedrock Engineering Soils
Predominantly Coarse Predominantly Fine Falls Rock Fall Debris Fall Earth Fall
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Topples Rock Topple Debris Slide Earth Slide Slides Rotational Rock Slide Debris Slide Earth Slide
Translational Lateral Spreads Rock Spread Debris Spread Earth Spread
Flows Rock Flow (Deep Creep)
Debris Flow Earth Flow (Soil Creep)
Complex Combination Of Two Or More Principal Types Of Movement The occurence of landslides is a result of the interaction of both natural and anthropogenic factors. The inherent geologic character of an area may contribute to its susceptibility to mass wasting (i.e. landslide, debris flow, rock fall). Most common triggering mechanisms for mass movement of materials are ground shaking (earthquake or due to a volcanic eruption) and excessive rainfall. Sometimes preexisting landslide susceptibilities are exacerbated by human activities which include deforestation (e.g., brought about by “kaingin” or slash-and-burn farming methods), steepening of the slope following road construction, and building of heavy infrastructures (e.g. houses, buildings, etc.) on slopes.
The underlying materials (i.e. soil, rock, fractured and weathered rocks) determine an area‟s susceptibility to mass wasting. Hence, loose materials such as soils and other non-cohesive aggregates are prone to mass wasting, in comparison to hard, non-fractured rocks (Sidle and Ochiai, 2006). The degree of weathering and the presence of fractures and foliations also exacerbate the tendency for slopes to fail. The presence of faults and activity along such structures initiate mechanical and chemical weathering which help to weaken the materials. Movement along faults also acts as triggers for landslides to occur. The planned field survey will look into the details of the geological controls in the area that could contribute to landslide susceptibility.
Slope gradient is a major factor to consider when assessing for an area‟s susceptibility to landslide. Generally, the steeper the slope is, the higher its likelihood for failure. Slope modification (eg. road cuts), often result in the over steepening of the slope, thus increasing its susceptibility to landslide.
The introduction of water into pore spaces contributes to the increased chance for slope failures. Hence, hydrological processes such as precipitation and infiltration have a major role on landslide initiation (Sidle and Ochiai, 2006). These processes are particularly important in slopes consisting of unconsolidated/loose earth materials (soils, sands, gravels). Oversaturation during extended periods of rainfall often trigger unconsolidated materials to act with fluid-like consistency, hence, moving faster downslope.
Based on the Modified Coronas Classification Map by the PAGASA (Fig. IV-28), the project site falls under the Type III climate. As such, wet and dry periods are not very distinct in this region but it is relatively dry between December to February or March to May and relatively wet during the rest of the year. Prolonged and heavy precipitation during the wet season may lead to landslides in the areas that are already predisposed to slope failures in terms of their geologic and geomorphic natures.
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Other contributing factors include the steepness of the slope and ineffectiveness or lack of the vegetative cover to hold the soil. Although landslides are primarily associated with mountainous regions, they can also occur in areas of generally low relief. In low-relief areas, landslides occur as cut-and-fill failures such as in roadway and building excavations.
The Mines and Geosciences Bureau of the DENR have previously evaluated the Angat
area for its landslide susceptibility. Their survey concluded that the areas immediately surrounding Angat Dam are moderate to highly susceptible to mass wasting (Fig. IV-29).
Figure IV-28. Map showing the different climate types in the Philippines: Type I = Two pronounced seasons which are: dry from November to April, and wet from June to September; Type II = No dry season with a very pronounced maximum rain period from December to February; Type III =No pronounced maximum rain period, with a short dry season lasting only from one to three months; and Type IV =Rainfall more or less evenly distributed throughout the year (Source: PAGASA).
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Figure IV-29. Landslide susceptibility map for the provinces of Bulacan and Rizal. The location of the Angat Dam is shown by the blue box (MGB, 2009).
The Department of Environment and Natural Resources-Mines and Geosciences Bureau has completed the geohazard assessment and mapping of the entire Philippines (DENR-MGB, 2011). These geohazard maps have been circulated to all local government units nationwide to aide them in their planning needs. Information and education campaigns (IEC) have also been conducted to raise awareness and preparedness for Geohazards (DENR, 2011). In Bulacan alone, MGB Regional Office III (MGB-R3) had already assessed 569 barangays in the province for flooding and landslide susceptibility.
To further substantiate the geohazard mapping efforts of DENR-MBG, this study generated hazard maps of the 3 towns immediately downstream of the Angat Dam through the use of GIS-based tools and multi-criteria analysis. These are the Angat, Bustos and Norzagaray towns. The use of GIS has proven its efficiency and versatility in facilitating fast and transparent decision-making for geohazards assessment applications (Manandhar, 2010). In terms of the context of hazard management, GIS can be used to create interactive map overlays that illustrate
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the spatial extent of hazards. Such maps can then be used to coordinate mitigation efforts before any disastrous events can occur (Raford, 1999 as cited in Awal, 2003).
This chapter aims to determine the extent of vulnerable areas at barangay level in relation to the landslide and flood hazards in the downstream communities of Angat Dam. Maps generated from the study will be useful in strengthening the local disaster risk reduction programsof these communities. In particulary, it can aid them in their planning for infrastructural developments, relocation plans and other appropriate interventions as well asimpact mitigation in the event of disasters.
Methodology
Mapping of geohazards in terms of flooding and landslide for the purpose of this study considered several physical parameters. Hazard analysis involves handling of voluminous data as input, hence, GIS offers the capability to standardize the analysis that can be done repeatedly until the desired result is achieved. The study involved vector and raster analysis based on the weights applied to each parameter using Analytical Hierarchy Process (AHP) to derive hazard index for both flooding and landslide. The creation of these maps was guided by the flow chart illustrated below (Fig. IV-30).
Figure IV-30. Hazard mapping flowchart of Angat, Bustos and Norzagaray, Bulacan
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Preliminary Data Acquisition
The data used in this study were acquired from existing maps and secondary data from various government agencies. The political boundaries within the study area used in this study were derived from their respective Socio-Economic Profile (SEP) and Comprehensive Land Use Plan (CLUP). Available shapefiles were also acquired from government institutions while the Digital Elevation Model (DEM) was downloaded from the Global Land Survey Digital Elevation Model (GLSDEM; http://glcf.umd.edu/data/glsdem/). Table III-3 shows the summary of raster and vector layers used in the study.
Table IV-3. Data Acquisition of the Study Data Layer Data Type Source
Political Boundary Vector (Polygon)
SEP and CLUP of Angat, Bustos and Norzagaray
Landuse Vector (Polygon)
DA-BARSAIL
Slope Raster Aster DEM 30m resolution
Elevation Raster Aster DEM 30m resolution
Fault Line Buffer Vector (Polygon)
PHIVOLCS Active and Liquefaction Susceptibility Map of Region III
River Buffer Vector (Polygon)
DENR-MGB Map Sheets (7172-I, 7272-IV and 7272-I)
Geology Vector (Polygon)
DENR-MGB Map Sheets (3164-I, 3264-IV and 3261-I)
Flooding and Landslide Susceptibility
Vector (Polygon)
DENR-MGB Map Sheets (7172-I, 7272-IV and 7272-I)
Preparation of Database
The political boundary, river system, fault line, geology as well as flooding and landslide susceptibility data layers were generated through georeferencing of available printed maps and then digitized using GIS. Database for slope and elevation factors were extracted from Aster DEM with 30 meter resolution using raster functions in GIS. Proximity analysis in terms of
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buffering was done in GIS for fault line and river system. All map layers were projected using World Geodetic System 1984 as datum and UTM Zone 51N as coordinate reference system.
Landslide and Flood Hazard Criteria
The landslide hazard criteria used in this study were presented in Table IV-4 and IV-5. In terms of mapping the landslide hazard, parameters such as land use, slope, elevation, distance from fault line (fault line buffer), geology and landslide susceptibility (DENR-MGB) were used. Similar parameters were also considered in flood hazard mapping except for distance from river (river buffer) and flooding susceptibility (DENR-MGB). Reclassification of the attributes on the said parameters has been employed using GIS.
All factors identified in hazard mapping comprised of subfactors based on the attributes of each layer. Ranking were done based on their relative influence on the occurrence of hazards using a rating scale of 1 to 4. However, there are two ways of assigning the rank for each subfactor such as straight ranking (1 as the most important and the 4 as the least important) and inverse ranking (1 as the least important and 4 as the most important).
Table IV-4. Factors for landslide hazard mapping
Factors AHP Weight
Subfactors Hazard Ranking
Landuse 0.028158
Developed Agricultural
Forested Grassland
3 2 2 1
Slope 0.290087
0-15% 15-45% >45%
1 2 3
Elevation 0.123793
<100 100-150
>150
3 2 1
River buffer 0.137677
< 1km 1-5 km 5-10 km >10 km
4 3 2 1
Geology 0.038126
Clastics Pyroclastics
Old Sedimentary
3 2 1
Flooding Susceptibility
0.38216
No Data Low
Moderate High
0 1 2 3
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Table IV-5. Factors for flood hazard mapping Factors AHP
Weight Subfactors Hazard
Ranking Land use 0.164774
Developed
Agricultural Forested
Grassland
3 2 2 1
Slope 0.127328
0-15% 15-45% >45%
1 2 3
Elevation 0.022379
<100 100-150
>150
3 2 1
Fault line buffer 0.07757
< 1km 1-5 km 5-10 km >10 km
4 3 2 1
Geology 0.19705
Clastics Pyroclastics
Old Sedimentary
3 2 1
Landslide Susceptibility
0.410899
No Data Low
Moderate High
0 1 2 3
A. Land use Factor
The land use factor was derived from available spatial data of Department of Agriculture – Bureau of Agricultural Research Spatial Analysis and Information Systems Laboratory (DA-BARSAIL). Ranking was based on the influenced of human activities on the given land uses, hence, land uses which is usually manipulated brought by human needs are susceptible on the occurrence of landslide and flooding. Land use maps of the study are shown in Fig. IV-31 to III-33.
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Figure IV-31. Landuse map of Angat, Bulacan
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Figure IV-32. Landuse map of Bustos, Bulacan
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Figure IV-33. Landuse map of Norzagaray, Bulacan
B. Slope and Elevation Factor
The slope (Fig. IV-34 to IV-36) and elevation (Fig. IV-37 to IV-39) factors were extracted from a 30-m Aster DEM using GIS. Areas with flat to gentle slope (<15%) and located in low elevation areas are susceptible to flooding. On the other hand, areas with moderate slope to steep slope (15% to >45%) at higher elevations are highly susceptible to landslide.
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Figure IV-34. Slope map of Angat, Bulacan
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Figure IV-35. Slope map of Bustos, Bulacan
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Figure IV-36. Slope map of Norzagaray, Bulacan
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Figure IV-37. Elevation map of Angat, Bulacan
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Figure IV-38. Elevation map of Bustos, Bulacan
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Figure IV-39. Elevation map of Norzagaray, Bulacan
C. Fault line Buffer Factor The traces of West Valley Fault according to PHIVOLCS maps were buffered at
specified distance using proximity analysis of GIS (Figure IV-40 to IV-42). Highest rank was designated for those areas near to the fault line while lowest for areas farther from the fault line.
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Figure IV-40. Fault Line Buffer map of Angat, Bulacan
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Figure IV-41. Fault Line Buffer map of Bustos, Bulacan
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Figure IV-42. Fault Line Buffer map of Norzagaray, Bulacan
D. River Buffer Factor
The river system used was derived from the hazard maps of DENR-MGB (Fig. IV-43 to IV-45) and it was also buffered at specified distance. Areas closer to the river system obtained the highest ranking since water level rise is expected to be highest at these areas. Thus, lower rank was assigned for areas farther from the river.
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Figure IV-43. River Buffer map of Angat, Bulacan
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Figure IV-44. River Buffer map of Bustos, Bulacan
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Figure IV-45. River Buffer map of Norzagaray, Bulacan
E. Geological Factor
Geological factor used in the study was derived from the DENR-MGB mapsheets (Fig. IV-46 to IV-48). The rock types identified on the mapsheets were grouped into categories based on their composition as basis for ranking such as clastics, limestone/pyroclastics and igneous/old sedimentary rocks.
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Figure IV-46. Geologic map of Angat, Bulacan (DENR, MGB)
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Figure III-47. Geologic map of Bustos, Bulacan (DENR-MGB)
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Figure IV-48. Geologic map of Norzagaray, Bulacan (DENR, MGB)
F. Landslide and Flooding Factors Landslide (Fig. IV-49 to IV-50) and flooding factors (Fig. IV-51 to IV-53) were
generated from landslide and flooding susceptibility map produced by DENR-MGB. Ranking of both hazards were based on the description identified by DENR-MGB in which area with high susceptibility hazards obtained a higher rank.
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Figure IV-49. Landslide Susceptibility map of Angat, Bulacan (DENR-MGB)
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Figure IV-50. Landslide Susceptibility map of Norzagaray, Bulacan (DENR-MGB)
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Figure IV-51. Flood Susceptibility map of Angat, Bulacan (DENR-MGB)
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Figure IV-52. Flood Susceptibility map of Bustos, Bulacan (DENR-MGB)
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Figure IV-53. Flood Susceptibility map of Norzagaray, Bulacan (DENR-MGB)
Analytical Hierarchy Process (AHP)
Through pair-wise comparison matrix (PCM) among the factors used in the study, individual weights were estimated using AHP which was developed by Saaty in 1980 (Table IV-6 and IV-7). PCM made use a scale of 1 to 9, with 1 being of equal importance and 9 of extreme importance. The Saaty Rating scale was presented in Appendix B. Results of the PCM will lead to the next step in AHP which involve derivation of consistency vectors and relative important weights (RIW) as shown in Table IV-8 and IV-9.
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Table IV-6. Pairwise comparison matrix for landslide hazard factors
The calculation of consistency ratio (CR) is important in the process of AHP because it determine the fitness of the estimated weights. The acceptable value of CR must be less than 0.10, otherwise revision of value judgments in PCM is needed. The following are the equations used in deriving the consistency ratio (CR) and consistency index (CI):
(Equation 2)
Where: CI – Consistency Index; RI – Random Index
(Equation 3)
Where: -average value of the consistency vector; n- total number of factors Table IV-10 presents the values of Random Index (RI) according to the number of factors used in AHP. The study employed six factors for both landslide and flood hazards, hence, the value RI used in the study is 1.24. Table IV-10. Random index values No. of Factors 1 2 3 4 5 6 7 8 9
Random Index
0 0 0.58 0.90 1.12 1.24 .32 1.41 1.45
Based on the computations, the derived CR and CI for landslide and flood factors of the study are acceptable since values obtained are less than 0.10 indicating high level of consistency (Table IV-11). Thus, the derived RIW (Table IV-8 and IV-9) are ideal in modeling the said hazards through GIS.
CR 噺 CIRI
CI 噺 岫ぢ 伐 n岻岫n 伐 な岻
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Table IV-11.Estimated CR and CI Factors Consistency ratio Consistency index
Landslide 0.069467488 0.086139685
Flood 0.063856908 0.079182566
Raster Overlay Analysis
The weighted linear combination was applied to derive the landslide and flood hazard index map of the study sites:
(Equation 4)
Where: 茎荊沈 - hazard index for area I 迎荊激珍-calculated weight for factor j 隙沈珍 - hazard rating of sub-factor i
Based on Equation 4, the hazard maps were derived using the following raster calculator expression in GIS:
Ground Penetrating Radar Introduction Geophysical surveys were done transecting the Angat Dam to search for any trace of the West Valley Fault within area. One geophysical technique carried out employed Ground Penetrating Radar (GPR) which is popular in mapping subsurface structures (Di Prinzio et al., 2010). This non-invasive method uses radar that transmits electromagnetic signals, specifically radio waves, into the subsurface that are reflected back to a receiver. Signal changes occur when they encounter a structure or change in material consistencies. The signals are recorded in a laptop computer where corresponding images of the signals are also displayed. These radar images undergo post-processing to improve the resolution to help emphasize structures and minimize noises that affect the images. The particular equipment model used in this survey uses the post-processing Prism 2.5 software. Methodology Survey lines were run from the east to the west at 30-meter long lines with a few meters of overlap (Fig. IV-54). The coordinates of the start and end points of each survey line were recorded using a handheld Global Positioning System (GPS) device. The GPR surveys in Angat Dam utilized the Georadar Zond-12-e which consists of a laptop computer, battery, control unit and antenna. The transmitter sends out signals through the antenna that are then reflected by the target body to the receiver (Fig. IV-55 and IV-56). Setups appropriate to the target can be manipulated through the computer attached to the controller. Data were instantaneously displayed on the computer during the survey. A 38 Mhz antenna was used during the GPR survey to achieve maximum penetration capabilities of the equipment which is 30 meters for most of the survey lines.
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Figure IV-54. Map showing the traverse that covered the GPR survey.
Sp
ill
wa
y
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Computer with
Prism 2 software
Synchronizer Stroboscopic
converter
Transmitter Receiver
Target
antenna antenna
antenna
FigurE IV-55. Schematic diagram of a GPR. The electromagnetic signals are controlled through the computer and propagate from the transmitter and eventually reflected back by the target to the receiver (modified after Radar System, 2007).
Figure IV-56.The Zond 12-e Georadar consists of a laptop computer, controller, power supply and antenna.
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Setup The configuration of the radar was set before the survey was done through the Prism 2.5 interface (Fig. IV-57). The parameters were adjusted to achieve maximum yields per survey line. These took into consideration the targeted depth of sounding, characteristics of the materials within the survey area and other antenna specifications and mode of surveying. Table IV-12. Parameters adjusted before surveying and some other setup options in Prism 2.5 (modified after Radar System, 2007).
Parameters Function/Description
Medium It displays a list of media which the user can select the closest medium observed in the area.
Stacking This refers to setting of number of traces (signal). It reduces noise and increase the depth rating
Scan rate This pertains to the traces per second which is automatically adjusted by the computer based on stacking selected.
Sounding mode This could be continuous or stepped. Continuous sounding sets the georadar to perform sounding until terminated in the computer. In stepped sounding, georadar will generate trace only if commanded in the computer.
Mode Select between sounding or testing modes o perform either formal survey or trials for the checking of the equipment.
Tx/Rx cables This is automatically set to “combined” when using 38-75-150 Mhz antenna.
Antenna This where the type of antenna used is specified for the computer to adjust.
Range Display a set of range based from proposed values for selection. This determines the interval of depth.
Gain Enhances the signals received through the image displayed. This function depends on the depth of penetration.
High pass filter Suppresses low-frequency signals which are usually produced when surveying on uneven surface.
Pulse Delay It helps maximize the observable signals.
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Figure IV-57. Screenshot of Setup window using Prism 2.5 software (adopted from Radar System, 2007). Data Processing Raw data obtained from the survey were post-processed to eliminate noise due to interference from the environment of the survey area. Data processing aims to extract necessary signals and enhance them to be more obvious or notable in the profile as they could correspond to a structure or feature. Noises include non-informative data that are removed or processed to be less notable for they may affect the interpretation.
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Table IV-13. Post processing options and operations in Prism 2.5 (modified after Radar System, 2007).
Post-processing Function/Description
Background Removal Removes horizontal line signals that do not changes throughout the sounding data which may mask real reflected signals.
Horizontal LP-Filters It is a low-pass which extracts slow variable signals and supresses fast variable signals.
Horizontal H-P Filters It is a high-pass filter which extracts rapidly varying signals and suppresses extensive signals.
Ormsbybandpass It filters low frequency interference and high frequency components of a signal.
Notch filters In case of an overlap with broad-band signal background, it suppresses narrow-band interference.
Moveout correction It eliminates errors in inclined distances.
Time-depth conversion It displays time profile as depth profile.
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3
Figure IV-58. Map showing representative survey lines east and west of the Watergate and on the spillway.
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GRAVITY METHOD
Introduction
A gravity survey was conducted traversing the road network along the northern embankment of the Angat Dam and the foot trail directly to its south. Both lines run east-west. This geophysical method serves as a useful guide in delineating the location of different geologic structures, e.g. faults and fractures. Information from the different densities of rocks, derived from the earth‟s gravity field, also provide an image of the subsurface to recognize the existence, extent and relationships between different geologic features.
Three base stations and 14 reading stations were occupied with a 300-meter interval between each station. A handheld Global Positioning System (GPS) was used as reference for distance estimates during the traverse. Base stations were established at preferred landmarks for beginning and ending readings. Station elevations were based on 1:50,000 topographic map published by the National Mapping and Resource Information Authority (NAMRIA) and a Suunto watch altimeter.
Following the usual gravity survey protocol, a single standard loop method was employed for the gravity study. Gravity measurements were gathered using a Scintrex CG-5 Gravitymeter with .001 mGal accuracy of readings. To record the coordinates of each station, a handheld GPS with an accuracy of ± 3 meters was used. Three gravity meter readings, elevation, time, coordinates, lithology, and description of station location were recorded at each survey station (Fig. IV-59 a and b).
After each survey, corrections for the gravity data were then applied to ensure that the varying densities observed in the data are from the signatures of the underlying rocks. The series of data reductions included drift correction, free-air correction and Buoguer correction.
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Figure IV-59 a)The gravitational field was recorded using the Scintrex CG-5 gravity meter. b) Location map of stations that were occupied during the gravity survey.
Data Corrections
To ensure that the gravity measurements are density variations of the subsurface lithologies and not from other sources, a series of data corrections were performed. This included drift correction, free-air correction and Buoguer correction. Other signatures that are otherwise not caused by the varying densities of the subsurface units are then eliminated.
Instrument Drift Correction
Throughout the survey, an error in measurements caused by temperature and mechanical induced fatigue and temporal changes in the elastic property of the gravity meter must be monitored. This refers to the instrument drift correction of the observed gravity measurements during the survey. Such correction accounts for a .01-.1 mGal difference in the readings. The time at which the gravity measurement was taken must also be noted for each station during the survey and reoccupation of the base station must also be periodically done. A linear variation is assumed between consecutive base station measurements and the computed correction for the instrument drift is evenly distributed to the other stations within each loop. The drift corrected data are now the values that would have been observed at each station had all measurements been taken at the same time.
Free-Air Correction
One of the elements that cause variations in the measured gravitational field is elevation. An increase in the elevation of a station with respect to the sea level as its reference implies an increase in the distance from the earth‟s centre of mass. This variation must be eliminated from the measured gravity by using the constant, .3086 mGal per meter (free-air correction) of elevation difference. This correction yields the free-air anomaly.
Bouguer Correction
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The Bouguer accounts for the approximation in the distribution of topographic masses for stations where the gravity fields were measured. An opposite effect with that of the Free-Air correction is given by this correction since the free-air correction is only for the difference in elevation with reference to the sea level and does not take into account the difference in the topographic masses between the station and the sea level. This effect must also be removed in order to compare the gravity measurements at each station. The Bouguer correction is computed using the formula:
Buoguer Correction = 2ヾとGh (Equation 4)
where と = density of the crustal rock (2.67 g/cm3), G = universal gravitational constant (6.67x10-11N-m2/k) and h = station elevation. The result of this data correction is the Bouguer anomaly.
Data
After the necessary data corrections were applied the resulting relative data Bouguer anomaly were plotted as profiles. Two profiles were generated from the two east-west traverses. These profiles are presented below to show the variations of the measured field. Each profile is discussed with the corresponding geologic cross section and details of the station location.
MAGNETIC METHOD Magnetic geophysical surveys measure the Earth‟s magnetic field, and with the proper
corrections, give anomaly values caused by the magnetic properties of the underlying rocks. It is commonly used in mapping igneous bodies and geologic structures involving lithologies with differences in magnetic susceptibilities.
A magnetometer is used in conducting magnetic surveys (Fig IV-60). For this survey, a Scintrex EnviMag Magnetometer system is used. It is a proton precession magnetometer basically composed of a coil surrounding a hydrogen rich fluid. Direct current is passed through the coil causing the protons in the fluid to align themselves with respect to the magnetic field produced. This induced current is interrupted and the protons realign themselves with the ambient magnetic field. The protons precess according to the intensity of the ambient magnetic field. The precession of the protons creates a rotating magnetic field, which is picked up by the receiver and subsequently amplified to produce field strength as the digital data.
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Figure IV-60. Magnetic surveying in Angat Dam
Figure IV-61. Location map of stations that were occupied during the magnetic survey.
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A magnetic survey was carried out to locate possible structures in the area of the Angat Dam. Fig. IV-61 shows the station location plot for the survey. Each station is placed approximately 300m apart. Readings for base stations of each loop were taken at intervals of less than two hours. Station locations and altitudes were both determined using a handheld GPS unit.
Reduction of magnetic data is necessary to eliminate causes of magnetic variations other than those caused by the subsurface. The following sections discuss the corrections applied for data from the magnetic survey of Angat Dam.
a. Diurnal variation correction
The diurnal variation correction is applied to account for the changes in the readings of instrument within a day. Correction for instrument drift (d) is measured by the subtraction of the final reading (rf) at the base station from the initial reading (ri) at the same base station, multiplied by the time elapsed (te) at the specific station, divided by the cumulative time (tc) of the whole survey, 穴 噺 堅捗 伐 堅痛建頂 建勅
By convention, the drift is assumed to be linear between base readings. b. Geomagnetic correction
Geomagnetic correction accounts for the magnetic field of the earth which is not caused by the underlying rocks. It is calculated using the formula of the International Geomagnetic Reference Field (IGRF). This formula defines the theoretical undisturbed magnetic field at any point on the Earth‟s surface. Due to the complexity of the formula, a computer is required to calculate large numbers of harmonics employed in the equation. The geomag70.exe is a command prompt based program which calculates the undistrurbed magnetic field at any point on the earth‟s surface. Data needed for the calculation of the IGRF are the date and time of survey, location coordinates and the altitude of the stations. This program can be freely downloaded from the International Union of Geodesy and Geophysics (IUGG) website.
Application of these corrections reduces the magnetic data to magnetic anomalies that are
used for interpreting the subsurface configuration.
