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Review of Related Literature “Flood Analysis in Mayorga, Leyte” (CE 483 Undergraduate Research)

TOLIBAS, TEJAY L. Student BSCE 4C

Street Floods in Metro Manila and Possible Solutions Alfredo Mahar Lagmay, Jerico Mendoza, Fatima Cipriano, Patricia Anne Delmendo, Micah Nieves Lacsamana, Marc Anthony Moises2, Nicanor Pellejera III, Kenneth Niño Punay, Glenn Sabio, Laurize Santos, Jonathan Serrano, Herbert James Taniza, Neil Eneri Tingin 1. National Institute of Geological Sciences, University of the Philippines, Quezon City 1101, Philippines 2. Nationwide Operational Assessment of Hazards Phil-LiDAR 1 Flood Modelling Component, UP NIGS, Quezon City 1101, Philippines

ABSTRACT Urban floods from thunderstorms cause severe problems in Metro Manila due to road traffic. Using Light Detection and Ranging (LiDAR)-derived topography, flood simulations and anecdotal reports, the root of surface flood problems in Metro Manila is identified. Majority of flood-prone areas are along the intersection of creeks and streets located in topographic lows. When creeks overflow or when rapidly accumulated street flood does not drain fast enough to the nearest stream channel, the intersecting road also gets flooded. Possible solutions include the elevation of roads or construction of well-designed drainage structures leading to the creeks. Proposed solutions to the flood problem of Metro Manila may avoid paralyzing traffic problems due to shortlived rain events, which according to Japan International Cooperation Agency (JICA) cost the Philippine economy 2.4 billion pesos/day. © 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. Introduction Metro Manila is located on an isthmus between the Manila Bay and Laguna de Bay. The entire region is composed of one major catchment called the Marikina River Basin, which covers 535 km2, and eight smaller, river sub-basins, which cover 683 km2 that drain directly into Manila Bay and Laguna de Bay. The Marikina, Pasig, San Juan and Tullahan rivers serve as the main outlets for a network of tributaries of the Marikina River Basin and smaller catchments of Metro Manila (Fig. 1). Highly urbanized and populated by almost 12 million residents (Cox, 2011), the metropolis lies on one of the widest floodplains in the Philippines. Apart from devastating floods like those spawned by Tropical Storm Ondoy in 2009 (Lagmay et al., 2010) and the typhoon- enhanced southwest monsoon rains in 2012, 2013 (Lagmay et al., 2014) and 2014, more frequent floods caused by short-lived thunderstorms are also a problem. Once parts of the road network are blocked by floods, traffic develops and paralyzes the entire city. According to JICA, traffic jams due to thunderstorm- related flashfloods costs PhP 2.4 billion a day from wasted gasoline and lost economic productivity (Rodis, 2014). Flashfloods are traditionally blamed on the loss of infiltration due to urban concrete, a centuryold drainage system, and clogged streams. This study analyses nuisance floods caused by brief,

heavy downpours. It identifies other factors to find relatively inexpensive solutions to floodgenerated traffic problems. Methods The Metro Manila Development Authority (MMDA) released a list of flood-prone areas in the National Capital Region, verified by accounts collected from photographs posted in social media. Crowd-sourced data were overlaid on a 100-year rain flood-hazard map. LiDAR-derived topography was used to create profiles of the main roads in these areas, as well as profiles of the road sides. A Roces Street and CP Garcia Avenue in the University of the Philippines (UP) were also examined. Field work was also conducted to check the drainage crossing the streets in those areas. Floods were simulated in FLO-2D GDS PRO using the St. Venant equations for continuity and momentum and the finite-difference scheme to compute flood velocities. accelerations. These are solved using the finite-difference scheme to get the velocity across the boundaries in eight potential flow directions of every grid element. The simulations used 1 × 1 m LiDAR-derived elevation data. The floodplains were delineated into catchment areas based on the flow direction and accumulation. Manning's coefficient of 0.03 was assigned to streams, which is the normal value for main channels (Chow, 1959), and 0.15 to the floodplains which are predominantly concrete. Inflow and outflow nodes were assigned based on where the water flows in from the upper watershed and out through the main stream channel. Rainfall is simulated as a non-point source carrying water throughout the model. Once floodprone areas were identified from the 100-year flood-hazard map, higher-resolution simu- lations in sub-basins of concern were conducted for short- lived thunderstorms. An hour of rainfall with intensities of 30–70 mm/hr was used to simulate thunderstorms. Observations, road profiles and flood simulations revealed the causes of street flooding and indicated appropriate solutions. Five sites have bridges (Appendix A): Philcoa, R. Papa, C-5 Bagong Ilog, Osmeña–Skyway, and Don Bosco. The street at Philcoa stands 3.8 m above the creek bottom with a rectangular, 2.37 × 4.4m culvert perpendicular to the road and two circular, 1 m-diameter culverts parallel to the road. R. Papa is 1.38 m above the creek bottom. In C-5 Bagong Ilog, the street is 3.92 m above the stream bottom. Along Osmeña–Skyway is a 22.3-m bridge 3.34 m below street level. A stream with its bed 4.5 m below South Luzon Expressway in the Don Bosco area is drained by a parallel 4 × 2.5-m drainage structure. Eight places do not seem to have drainage networks, which could be masked by overlying concrete. Conclusions Metro Manila's floods are compounded by many factors including encroachment of concrete surfaces, densification of buildings and residential areas, silting of riverbeds and canals, obstruction of waterways by informal settlers, clogging of floodways by garbage, narrowing of rivers due to development on floodplains, draining and filling in of small rivers forcing more water into fewer channels, forest degradation, and reclamation of coastal land. Furthermore, humans have altered the landscape in the metropolis which has grown rapidly but with poorly planned urbanization. Since the 1970's, people have migrated from rural areas to Metro Manila increasing the population from 4.9 million residents in 1975 to more than 11 million today. A survey by the

National Housing Authority showed that by the early 1980s, a quarter of Metro Manila residents were informal settlers living in crowded shantytowns many along waterways. Further complicating the problem is ground subsidence. From 1978 to 2000, parts of Metro Manila sank by an amount ranging from 16 cm to 1.46 m. The probable causes of subsidence are excessive groundwater extraction, soil compaction and tectonic movement, though more research is needed to fully determine the primary causes (Lagmay et al., 2010).

Flood risk analysis for the Municipality of Bay, Laguna, Philippines EDUARDO C. CALZETA1, FELINO P. LANSIGAN2, LEONARDO M. FLORECE3, NATHANIEL C. BANTAYAN4 and RENATO L. LAPITAN5

An integrated approach was employed to analyze the riskiness of the Municipality of Bay, Laguna, Philippines to flood. The study was specifically undertaken covering the 10 low-lying barangays of the municipality, namely: Calo, Dila, Maitim, San Agustin, San Antonio, San Isidro, San Nicolas, Santo Domingo, Puypuy and Tagumpay. Elements of risk such as hazard, exposure, vulnerability and adaptive capacity were assessed and integrated in the context of socio-ecological framework. Analyses showed that Barangay Tagumpay is the mostrisky barangay to flood with 0.26 risk index among the 10 barangays assessed. It is followed by Barangay Maitim with 0.20 flood risk index. Barangays San Isidro, Dila, San Agustin, San Nicolas, San Antonio, Puypuy and Calo have moderate levels of risk with index ranging from 0.10 to 0.17. On the other hand, the least risky barangay is Santo Domingo with only 0.08.

Applying risk in flood assessment studies was employed by Ikeda (2006), Barredo, De Roo & Lavalle (2007), Kannami (2008), Zonensein et al. (2008), Bhattacharya (2010), Fano (2010), Okazawa et al. (2011) and Balica (2012). Kannami(2008) established a country-based flood risk index of the 235 countries and regions by combining the hazard, exposure, vulnerability and capacity indicators. He further categorized coping capacity into soft and hard measures. Results revealed that Haiti had the highest flood risk index of 4.5. It was followed by Bangladesh with 4.0 flood risk index. The third to eight spots are occupied by African countries such as Mozambique and Gambia. Philippines is ranked eleventh most risky with 2.7 flood risk index. Similarly, a detailed assessment was conducted in the Philippines by Fano (2010) adopting the same approach. Among the 82 provinces assessed, the province of Metro Manila emerged as the most risky to flood with the highest flood risk index of 3.22 due to its high vulnerability and exposure. MATERIALS AND METHODS Study area. Bay is one of the towns surrounding Laguna de Bay and bounded by the Municipalities of Los Baños in the northwest, Calauan in the southeast and Sto. Tomas and Province of Batangas in the western portion (Figure 2). It has a total land area of 4,080 has. and classified as second class municipality. Of the total of 15barangays, 10 were selected as case-study areas which are situated in the low-lying elevation of the municipality and near the lake as shown in Figure 2. These include the Barangays of Calo, Dila, Maitim, Puypuy, San Isidro, Santo Domingo, San Agustin (Poblacion), San Nicolas (Poblacion) and Tagumpay. Among the sampled barangays, Puypuy has the largest total land area with about 734.08 has while San Nicolas is the smallest. Barangay San Antonio is the most populated with a total of 5,563 inhabitants, while barangays San Nicolas and San Agustin have the smallest number of residents with only 1,341 and 1,397, respectively (National Statistics Office (NSO) 2010).

Flood risk indicators and parameters. Among the indicators and parameters assessed in this study are presented in Table 1. In this study, the extent and probability of occurrence of flood was estimated based on the computed discharge for Bay/Cambantoc watershed for certain return period. Flood map at different return periods were derived based on the developed unit hydrograph and calibrated Soil Conservation Service run-off equation by Calzeta (2013) for the Bay/Cambantoc watershed. Population density and inventory of household properties like vehicle, furniture and appliances were used as indicators for exposure. Vulnerability indicators measured in this study were poverty, illiteracy, presence of children, aged and disabled, and house structural type. In terms of adaptive capacity or resilience, indicators assessed were resident’s ability to swim, level of knowledge, awareness and preparedness to flood. CONCLUSION AND RECOMMENDATIONS Assessment of the degree of risk of 10 low-lying barangays of Bay was done in the context of socioecological framework. The elements of risk considered in the analysis were hazard, exposure, vulnerability and resilience. Index was used in the analysis to merge social and ecological indicators and quantify levels of risk. Results showed that barangay Tagumpay is most flood-prone with 0.92 hazard index, while barangay Puypuy is the least prone with only 0.31 hazard index. Barangay San Agustin is the most exposed barangay with exposure index value of 0.62 due to high population density. On the other hand, Barangays Puypuy, Dila and San Antonioare the least exposed with only 0.45, 0.46 and 0.48 exposure index, respectively. Highly vulnerable barangay is Maitim with the highest vulnerability index of 0.50 while Barangays Calo and Santo Domingo are least vulnerable with only 0.28 and 0.29 vulnerability index, respectively. Although barangay Puypuy has less probability of occurrence of flood due to its location, it has higher vulnerability due to lower literacy rate of the residents and low quality of the house structures in the area. Nine of the 10 sampled barangays have higher level of resilience or adaptive capacity to flood. Only barangay Puypuy has lower resilience index of only 0.58. In terms of flood risk, barangay Tagumpay is the mostrisky with the highest flood risk index of 0.26. It was followed by barangays Maitim with 0.20 flood risk index and San Isidro with only 0.17. Barangays Dila, San Agustin, San Nicolas, San Antonio, Puypuy and Calo have moderate levels of risk with flood risk index values ranging from 0.10 to 0.16. Among the 10 barangays assessed, Santo Domingo is the least risky to flood with only 0.08 flood risk index. Results of this study could serve as information to policy-makers, planners and executives in prioritizing efforts and resources to address flooding and minimizes its adverse impact. This study has identified areas that are at high risk to flood and which require immediate attention. Likewise, local executives can also assess which elements of risk need to be addressed to reduce impacts of flood. These can also serve as basis for future land use plans and institutional developments.

A Study on Flood Control System Introducing Storage Tank in Manila City Hall Area John Harold S. Castro, Glenda Aiselyn T. Badenas, Wennie M. Caldit, Donamel M. Saiyari, Brian G. Eurolfan Department of Civil Engineering, College of Engineering, Adamson University, Ermita, Manila, Philippines

The low-lying topography, meteorological and hydrological conditions of the Metropolitan Manila makes it vulnerable to floods and storm water Various measures have been conducted for mitigation of flood and inundation damages, but the drainage problem is still one of the major tasks. Historically, Manila suffered major floods that occurred in 1940’s to 1980’s. The flooding inflicted serious damage over the past half-century; these floods have become both more extensive and more severe as experienced in recent storms such as Ondoy and Habagat. In order to address the problem, different engineering works were utilized to provide flood protection and reduce flood damages. One alternative flood control measure is the provision of retarding basin for the purpose of reduction of the peak discharge of flood. Based on the hydrological, topographic and flooding information gathered from government and private institutions, a storage tank facility is proposed as alternative flood control measure in the study area to reduce the flood level and to identify the volume of the proposed storage tank. The conceptual simplified model for detention tank simulation model has been used to simulate the operation of the tanks and to evaluate the performance of the proposed structure.

METHODOLOGY The design discharge can be estimated by specific discharge method or runoff model using rainfall data. The runoff model was used in the study to compute urban runoff and flooding in the study area. For the purpose of this study, the two models were initially simulated with and without the storage tank component in the existing drainage system to observe the response of hydrograph and discharge results for storm event Ondoy occurring over the Estero De Balete Creek. Each runoff model was used to evaluate the effect of flood control to the initial design discharge. The characteristics in terms of size of the storage tank were determined to accommodate the excess discharge that occurred along the area where flooding was observed. In this study, Storm Water Management Model (SWMM) was utilized for runoff computation(Metcalf and Eddy, 1971; Huber et al., 1992). The procedures to evaluate the effects of detention storage used in this study includes inputting the geographical and physical data, estimation of coefficients for sub catchment areas and conveyance elements. Finally, the effect of the flood control in the study area was determined by comparing the hydrograph of the existing drainage system without storage tank with the hydrograph of the drainage system with storage tank component. SWMM is a distributed model, which means that a study area can be subdivided into any number of irregular subca tchments in manner to best capture the effect that spatial variability in

topography, drainage pathways, land cover, and soil characteristics have on run off generation. According to Huber et al. in 1992, EPA Storm Water Management Model (SWMM) is a comprehensive mathematical model for simulation of urban runoff quantity and quality in storm and combined sewer systems. All aspects of the urban hydrologic and quality cycles are simulated, including surface and subsurface runoff, transport through the drainage network, storage and treatment. SWMM is a physically based, discrete-time simulation model. It employs principles of conservation of mass, energy, and momentum wherever appropriate. This study considered the following physical processes which SWMM uses to model storm water runoff quantity such as surface runoff, infiltration and flow routing.

CONCLUSIONS Based on the abovementioned results, this study concludes the following: 1. The largest feasible volume of the detention tank based on rainfall intensity within the area is 50,000 m3. (A = 5,000 m2 x depth = 10 m); 2. The results of the simulation showed that the tank significantly reduced the flooding in the area during extreme storm event like Ondoy, inevitably, the design size of the tank cannot totally eradicate the flooding in the area during such event; and 3. Based on the available the location, the researchers chose to locate the tank outside the study area situated in the Luneta Park since the area can accommodate the construction of such large structure and due to its proximity to the nearest natural bodies of water for discharging point.

Flood Risk Assessment of the Antiao River Control Project in Catbalogan City, Philippines Ronald L. Orale ABSTRACT Flooding in Catbalogan City, Samar Philippines is perennial. Factors causing floods are due to increasing population, outdated and non-functional drainage system, heavily silted and reduced river size, poor waste management, no erosion control measures, reduced vegetative cover and the unusually heavier precipitation. In response to this flood problem, the local government asked help from the Department of Public Works and Highways which in turn developed a Flood Management and Drainage System Master Plan wherein a River Control Project which includes disilting of almost 2km stretch of the river and the construction of river walls are currently being implemented. Using a hydrologic modeling system (HEC-HMS) version 4, river discharge was calculated for at least 4 extreme events. Results have shown that the project will not solve the flooding problem due to extreme precipitation. The river walls are more needed upstream than downstream portion of the river while the disiltation of the river is not enough to carry storm water. There is therefore an urgent need to construct river walls in the upstream as well as other interventions specified in the master plan to manage the flooding problems in Catbalogan. Methodology: The methods used to answer the research question includes watershed profiling, characterization of precipitation in Catbalogan City, runoff and discharge analysis, river control project assessment and the flood risk calculation. Interviews, participatory rural appraisal and observation were also conducted to validate data gathered in the analysis. A. Watershed Profiling The profile of Antiao watershed was determined with the aid of National Mapping and Resource Information Authority (NAMRIA) topographic maps. The said map was used to identify the boundaries of the watershed including the tributaries supplying water to the river. Soil classification was derived from the Bureau of Soils and Water Management (BSWM) geological and soil maps. The determination of ground cover of the Antiao Watershed was estimated using rasterized satellite images from www.bing.com. These maps were analyzed by overlaying it with the NAMRIA maps in AutoCad environment. B. Characterization of Precipitation in Catbalogan Daily rainfall data came from the Catbalogan station of the Department of Science and Technology (DOST)-Philippine Atmospheric, Geographical and Astronomical Services Administration (PAGASA). Thirty years of monthly data was used as reference of normal precipitation volume. Five years of daily rainfall data was evaluated to determine extreme

rainfall events. Number of days with relatively continuous rains as well as the accumulated amount of rain was presented in histogram. C. Runoff and Discharge Analysis The runoff and discharge analysis made use of the Hydrologic Modeling System (HEC-HMS) Version 4, developed by the US Army Corps of Engineers-Institute for Water Resources Hydrologic Engineering Center. Variables used are based on runoff curve number (CN) method proposed by the United States Department of Agriculture (USDA) Technical Release 55 (TR55) published in June 1986. Simulation run using the HEC-HMS software was performed using daily rainfall data on selected months with extreme precipitation events. The simulation run is capable of estimating behavior of the modeled watershed given hydrologic information. Conclusions and Recommendations Catbalogan Samar in the past decade have experienced perennial flooding primarily due to extreme rainfall events usually occurring during a storm. In the past five years, Catbalogan has experienced more than half of the total number of months having precipitation larger than the 30 year normal. Based on the simulation, the river on the upstream part specifically along the vicinity of Bliss Community and San Andres in Catbalogan City cannot carry surface runoff from an extreme precipitation event. On the other hand, the river in its natural state near the Antiao Bridge is more than enough to carry precipitation as high as that which was experienced in December 2014. The Antiao River Project near the Antiao Bridge has increased the capacity but the same was not needed. On the other hand, disilting activity along Bliss Community will not solve the risk of flooding from extreme events. The walls constructed narrows the width of the river therefore an increase in water level is expected. This in turn may cause upstream water to increase. This possibility needs to be examined thoroughly. Heavy siltation is expected during an extreme precipitation event which reduces river carrying capacity. Disilting activity must be made regularly, at least ever after every extreme precipitation events. Soil erosion in the watershed needs to be addressed to reduce siltation and avoid clogging of the river. The river control project should have been implemented in the upstream side of the Antiao River and not near the mouth. To minimize the risk of flooding in the upstream side construction of river wall needs to be extended up to Barangay San Andres.

Flood Risk of Metro Manila Barangays: A GIS Based Risk Assessment Using Multi-Criteria Techniques Karlo P. Pornasdoro, Liz C. Silva, Maria Lourdes T. Munnariz PhD, Beau A. Estepa, Curtis A. Capaque

ABSTRACT This study examined the flood prone areas within Metro Manila to find out their degrees of disaster risk. More specifically, the study considered the population densities of Metro Manila barangays, the smallest political units of the country, the gender and age population, the structural materials and the recorded depths of flooding. Geographic Information System (GIS)using multi-criteria techniques was the tool of analysis of the study. Projecting the population density of each barangay, the children, elderly and women populations to 2020 and 2030 and simultaneously examining the recorded depths of its flood waters and existing structural materials, the study identified the barangays that will be at high risk by 2020 and 2030. Although the study is limited to population data and physical characteristics of barangays, the findings may be useful to urban and regional planners and government agencies involved in disaster risk reduction and mitigation management. The study can be integrated in future development plans of specific areas and be used to guide future flood control measures. Finally, the study may be considered by other countries in their analysis of similar flooding experiences. METHODOLOGY In the flood risk assessment of Metro Manila barangays, the following major steps for data collection and analysis were considered: First, data gathering of the relevant GIS layers were taken from different government agencies like the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) and the Mines and Geosciences Bureau (MGB) for the flood hazards of Metro Manila; the Metropolitan Manila Development Authority (MMDA) and the National Mapping Resource and Information Agency (NAMRIA) for the boundary maps of cities and municipality in Metro Manila; and the Open Street Maps (OSM) for other map requirements. Population data were gathered from the National Statistics Office(NSO). Barangay structural materials were taken from the 2003 Metro Manila Earthquake and Impact Reduction Study (MMEIRS). Second, the establishment of the base map and Geographic Information System (GIS)1 database of the study used the Digital Elevation Model (DEM) of Metro Manila with its surrounding provinces. Then, other layers, i. e., the updated city/municipality boundaries, and the GIS vector layers: waterways, roads and buildings, were overlaid for reference purposes. The Philippine Reference System (PRS92) was used as the Coordinate Reference System for all the layers. In determining the spatial characteristics that existed between datasets of barangays, the collected data were considered in the base map as different variables, but interacting with each other. The flood layers adopted the number of divisions by the Mines and Geosciences Bureau (MGB) (2013), which were VERY HIGH, HIGH, MODERATE, LOW and VERY LOW frequencies. Third, the study utilized a multi-criteria technique, where the environmental and social risks of barangays were examined. Based on the Framework, 5 indices were considered, namely: population density, gender, age, structural materials and flood depths; where, the gender and age indices were with respect to 3 population groups, i. e., women, children and elderly, the most vulnerable groups to floods. The women population data was females from 15 to 64 years old; the children population data was from 0 to 14 years old and the elderly population data was from 65 years old and above. It is noted

that NSO data for these specific groups were available only for city/municipality level and none for barangay level. CONCLUSIONS AND RECOMMENDATIONS The study cannot be said to be without limitations. Nevertheless, a GIS-based risk assessment of multiple criteria can improve the accuracy of flood risk assessment for Metro Manila with the consideration of the smallest political unit of Philippine society, the barangay. Firstly, the study shows barangays that can be at high and very high flood risks in the near future and in a relatively more distant future, and has implications to the disaster risk mitigation/reduction policies of LGUs. For instance, with the Marikina River rising as high as 21 meters during heavy downpours, the Marikina City government implemented structural mitigation programs through a number of flood-control projects and raised public awareness and emergency preparedness through a Disaster Management Office, i. e., Rescue 161 (Ordinance 264 of 1998) and a Disaster Preparedness Education Center, where a disaster management library for children and adults is one of its components (Asian Disaster Preparedness Center, 2008). However, these could be said to have been a response to the earlier experiences of the City. To know a few years earlier which barangays in Marikina City can be expected to be at high and very high flood risks can give the city government ample time to plan its future disaster risk reduction/mitigation programs and sustain its environment policies on public safety and quality of life. Furthermore, the city government can give priority interventions and determine some not too expensive flood mitigation strategies that can support the concerned barangays. Secondly, the study can be used by the national government, say, in the prioritized projects of the Department of Public Works and Highways (DPWH) and the MMDA that are within the flood control master plan, to solve perennial flood problems in Metro Manila (Manila Bulletin, 2012). Thirdly, both national and local governments can use the study as a guide to determining priority areas for future urban plans. Finally, as mapping can provide critical information at the barangay level, GIS- based mapping agencies can use the findings of the study to facilitate improvements in their output.