The process began with a collaboration with the University of the Philippines (UP) Diliman, where environmental engineering students assisted in designing a survey targeting about 200 households in flood-prone areas. This survey included questions about the frequency of flooding, depth of water during typhoons, health concerns related to stagnant water, and existing coping mechanisms.

Additionally, local volunteers, including high school students from nearby schools, participated in structured site assessments of key drainage points along Barangay 1 and 2, where drainage systems were known to be inadequate.

Each volunteer was trained to use measuring tools like water level gauges and GPS devices to document drainage capacities and identify specific blockages caused by debris or improper waste disposal. They recorded data on the size and condition of drainage outlets and noted areas where the infrastructure failed during recent heavy rainfalls.

We also utilized rainfall data from the PAGASA to analyze historical precipitation patterns, identifying trends in rainfall intensity that correlated with flooding incidents over the past decade. These data points were compiled into a centralized database, providing a foundational understanding of the stormwater challenges in Tondo.

Next, we used machine learning and data modeling to analyze the data collected from Tondo's stormwater management assessments. Using Python programming, a group of computer science students from UP Diliman, led by chapter director Jose, developed a predictive model that incorporated variables such as historical rainfall data, drainage capacity measurements, and flood depth observations from the previous year.

The team inputted over 500 data points into the model, which used random forests to identify correlations between rainfall intensity and flooding occurrences. They focused particularly on the impact of sudden downpours during typhoons, aiming to simulate various storm scenarios based on recorded precipitation patterns.

We then validated the model by cross-referencing its predictions with past flooding data collected during Typhoon Karding, allowing the team to assess its accuracy. For instance, the model successfully predicted flooding at specific locations in Barangay 1 with a 90% accuracy rate based on rainfall exceeding 200 mm within a 24-hour period.

Furthermore, we used simulations to visualize drainage flow under different scenarios, using HEC-RAS to model water movement through the urban landscape. This analysis highlighted critical chokepoints in the drainage system where interventions would be most effective.

Next, the team distilled their key insights and identified solutions by closely examining the results from their data analysis and simulations. We pinpointed 3 critical short-term interventions and 1 long-term strategy to mitigate flooding in Tondo.

The insights revealed that the most vulnerable areas were the low-lying informal settlements, including those in Barangay 1, where poor drainage systems and high population density exacerbated flooding. The team noted that over 60% of the surveyed households experienced water intrusion during heavy rainfall. We came to a consensus on 5 key solutions based on these findings.

The solutions were prioritized based on their feasibility, viability, desirability, cost-effectiveness, and relevance.

2. Implementing bioretention systems, culturally adapted rain gardens, rainwater harvesting systems, and permeable pavements to manage stormwater at its source and reduce runoff.
   

3. Developing flood-resilient housing to provide safe shelters for residents during severe weather.
   

4. Creating green spaces, including community pocket parks, vegetation, micro ponds with biofiltration, modular urban wetlands, and permeable green alleys to enhance local ecosystems and reduce surface water.
   

5. Drainage monitoring using Arduino-based sensors to track real-time water levels and predict flood risks with ML.
   

6. Prioritizing accessibility to evacuation centers.
   

We began by building bioretention cells (rain gardens) and culturally adapted rain gardens in Tondo, targeting the streets and alleys around Don Bosco and Happyland. Working closely with local craftsmen and botanists from UP Manila, we designed bioretention areas using native plants like Vetiver grass, Talahib, and Balanti, known for their high water absorption capacity. These rain gardens were strategically placed near community centers and Tondo High School to capture and absorb rainwater runoff.

For rainwater harvesting, we installed rooftop catchment systems on local community centers. These systems channeled rainwater into large underground storage tanks donated by Maynilad Water Services, ensuring that the harvested rainwater could be used during dry periods or for emergency purposes.

Student volunteers, who helped build both installations, regularly recorded data on water levels in the storage tanks and the health of the plants in the bioretention areas. This was part of a citizen science project, with students using simple tools like rain gauges and moisture meters to gather information. The data was then fed back into our ongoing research to refine and optimize the implemented solutions.

We began by identifying the most flood-prone areas around Don Bosco and Happyland through detailed site assessments The design phase involved collaborating with engineering students from UP Diliman. These homes were designed to be elevated on stilts made from locally-sourced bamboo and reinforced with concrete for additional stability. The elevated structures helped to keep living areas above the typical flood level, significantly reducing the risk of water damage during heavy rains and typhoons.

To ensure affordability and community buy-in, we sourced materials such as bamboo and concrete through local suppliers and received donations from construction company DMCI Holdings. The construction process was highly participatory, with training sessions for residents on how to build and maintain their new homes. High school students from Tondo High School and local vocational training institutes also helped during thi process. The homes also featured flood-proofing measures, such as water-resistant coatings on walls and floors, and built-in rainwater harvesting systems to manage runoff effectively.

In the dense, flood-prone areas of Tondo, we focused on creating green spaces by collaborating with local urban planners and students from UP Diliman to identify suitable sites.

Our efforts began with transforming 12 small, unused plots into community pocket parks. These parks featured native vegetation like Narra, Molave, and Kamagong trees, known for their robustness and ecological benefits.

We also introduced micro ponds with biofiltration systems to manage excess rainwater, using aquatic plants like Water Hyacinth and Duckweed to filter contaminants.

We established modular urban wetlands in larger vacant lots, using bamboo and recycled materials for construction. These wetlands included walking paths and seating.

Additionally, we created small-scale, permeable green alleys by offering materials and technical support to residents willing to convert their concrete alleys into green corridors. These alleys were planted with resilient ground cover plants like Peanut Grass and designed to allow rainwater to permeate, reducing runoff and flooding. Throughout the project, students and volunteers played an active role, from planting vegetation to constructing biofiltration ponds.

To effectively monitor and manage stormwater runoff in Tondo, we implemented an innovative smart drainage monitoring system. Partnering with engineering students and professors from UP Diliman, we designed and deployed Arduino-based sensors throughout the neighborhood. These sensors were installed in drainage canals near Don Bosco and Happyland to collect real-time data on atmospheric and climatic parameters including rainfall intensity, water levels, and flow rates. Students from Tondo High School were trained to assemble and maintain the sensors, making use of low-cost materials sourced from local electronics shops.

The data collected by these sensors was transmitted to a central server, where it was analyzed using machine learning algorithms to predict potential flooding events and identify drainage chokepoints. The predictive models were validated and refined through simulations run on UP Diliman's computational resources. This monitoring system not only provided actionable insights for immediate response to rainfall events but also informed long-term infrastructural planning by highlighting areas requiring urgent upgrades.

In our strategic planning for large-scale water infrastructure redevelopment in Tondo, we identified critical flood-prone areas through community mapping sessions and consultations with local NGOs, particularly focusing on neighborhoods like Happyland and the Tondo Foreshore.

Our proposal emphasizes the need for a resilient drainage system that integrates bioretention basins and permeable pavements, designed to handle extreme rainfall events, as demonstrated by historical flooding patterns during typhoon seasons, using our existing installations and their positive impact on Tondo as case studies.

We're also advocating for the creation of community-managed retention ponds, using low-cost materials sourced locally to enhance community ownership and reduce costs through a phased approach, starting with pilot projects in high-traffic areas, to assess effectiveness before wider application.

The plan also includes recommendations for elevating critical roadways and pathways to mitigate flood risks, ensuring accessibility even during heavy rains. Our goal is to submit this comprehensive redevelopment proposal to the local government and other stakeholders, advocating for funding and support to improve Tondo's resilience to typhoons.

Our goal is to secure funding from both governmental and non-governmental sources, proposing that investments be matched by community labor and materials, thereby reducing costs and fostering local engagement. We aim to present this comprehensive redevelopment framework to the city government, advocating for policy shifts that prioritize sustainable urban water management.