As a tropical country, Indonesia is a region prone to flooding because it has a relatively high rainfall intensity. Many urban areas grow in low-lying and coastal areas, resulting in a high vulnerability to water hazards (Handayani et al., 2020). Environmental degradation and climate change can exacerbate the possible impact of these disasters.

Indonesia has changed the paradigm of disaster management in the last dozen years (Djalante et al., 2012). A proactive approach has become a major concern for reducing the risk of natural disasters (including floods). Therefore, mitigation measure become an integral part of urban planning.

However, reducing the risk of flooding still faces various challenges in line with uncontrolled urbanization. Several studies have shown that flood inundation caused damages in densely populated areas (CFE-DM, 2018). Past disasters should be a lesson for future disaster preparedness because these hazards have a certain return period (Sudiar, 2013). Therefore, the main issue that we raise in this project is ineffective disaster management in adaptive aspect associated with physical loss caused by flood. Understanding flood damage based on historical events and actual data forms an important foundation in disaster management practice.

1. Community that live in flood-prone area
Flood disasters often cause fatalities, damage to houses, disruption of socio-economic activities, and other negative impacts. Physical loss can occur in communities with various socioeconomic status, both high and low income groups.

2. Government
Floods can destroy public facilities and cause significant economic losses. The government can even be overwhelmed to restore the situation if a flood disaster occurs on a high intensity scale.

3. Investor
Floods cause disruption to economic activity. Furthermore, investment interest will be lower if flood management is not effective.

Based on our analysis, there are two main causes for this problem.

First, lack of detailed flood loss data that is needed for urban planning resilience. In Indonesia, this data is poorly documented and few studies have examined the topic (Wijayanti et al., 2017; Tarigan et al., 2017). In fact, damage assessment is an essential element for developing flood management strategies.

Second, lack of capacity and awareness. Local communities are often not involved in disaster management efforts. A participatory approach is key in providing valuable data for policy making.

According to Indonesian Disaster Management Agency (BNPB), one of the main risk of physical loss is due to flooding (i.e., approximately US$12 billion). According to the BNPB database, the frequency of flooding tends to increase and the number of houses damaged or destroyed by floods reaches more than 50,000 units during 2010-2019. However, the database does not have specific information regarding loss estimation and disaster characteristics, both of which can be useful as a disaster mitigation evaluation tool. In this project, we shall interview flood-affected communities in Indonesia and develop depth damage curve (DDC) for flood assessment.

DDC (also known as stage damage function or vulnerability curve) shows the relationship between the maximum flood depth and the damage percentage (ratio of the cost of repairs to the market value of the building). It is very useful for evaluating flood control (Romali et al. 2015). However, this approach is rarely used in disaster assessment in Indonesia. Lack of historical flood data also made it difficult to construct accurate functions. Therefore, crowdsourcing-based data collection is used to obtain actual data after a disaster occurs.

• CFE-DM (2018). Indonesia Disaster Management Reference Handbook. Jakarta: CFE-DM.
• Djalante, R., et al. (2012). Building resilience to natural hazards in Indonesia: progress and challenges in implementing the Hyogo Framework for Action. Natural Hazards, 62, 779-803.
• Handayani, W., et al. (2020). Urbanization and increasing flood risk in the Northern Coast of Central Java—Indonesia: An assessment towards better land use policy and flood management. Land, 9(10), 343.
• Romali, N. S., et al. (2015). Flood damage assessment: A review of flood stage–damage function curve. In: Abu Bakar, S., et al. (eds). ISFRAM 2014. Singapore: Springer.
• Sudiar, N. Y. (2013). Analisis periode ulang banjir di Kota Padang menggunakan cara Iwai dan kaitannya dengan MJO (Madden Julian Oscillation). Sainstek: Jurnal Sains dan Teknologi, 5(2), 103-110.
• Tarigan, A. P. M., et al. (2017). A study on the estimation of flood damage in Medan City. MATEC Web of Conferences, 138, 06010.
• Wijayanti, P., et al. (2017). Estimation of river flood damages in Jakarta, Indonesia. Natural Hazards, 86, 1059-1079.

We believe that this problem can be improved by increasing community awareness and behavioral change by doing self-report of flood characteristics and damages. Detailed data and information are very important for any decision-making. If this project is successfully applied on a large-scale, it can provide benefits from the aspects of cost, labor, and time, during the disaster assessment.

Therefore, we propose to establish a platform to collect data (i.e., maximum flood depth and damage percentage) using the crowdsourcing method. The output is an empirical curve of the actual damage information, which is more accurate than the subjective what-if analysis (Pistrika et al. 2014). The data obtained can also be used for other purposes. For example, flood depth data can be used to validate flood hazard / inundation modeling, while damage data can be considered for claim relief assistance.

This approach will have impacts because of some reasons.

First, we will integrate our idea with local community who have awareness towards disaster and urban issues.

Second, this project highlights the importance of community participation or volunteering during disaster assessment. The successful implementation of urban planning based on disaster risk management is also determined by the support between stakeholders, emphasizing the importance of participatory approach.

Third, we can evaluate existing flood risk reduction efforts, so that we hope it will be better in the future.

There are some key metrics that can be used to measure the impact and performance of this project:

1. Survey on the user twice a year,
2. Evaluation of member participation and activity,
3. Disemination with the government,
4. Conduct focus group discussion (FGD) with government and community, and
5. Making publications from the results of data processing that can be accessed openly.

1. Urban enthusiast or youth community that has a vision to tackle urban problems, climate change, etc. They can engage and promote this project to the community to increase the level of participation.
2. Research institutions who have the same interest for developing flood loss assessment. This will be a great opportunity for researchers to improve on traditional assessment techniques.

Property developers and large business managers will likely oppose the project since they often refuse to provide detailed information due to data privacy and other reasons (for instance, see Wijayanti et al. 2017). People who are unfamiliar with smartphone technology or have poor digital literacy are also seen as unprepared to participate.

Our Personna: Kophi (Youth Green Coalition), TDMRC (Tsunami and Disaster Mitigation Research Center), BNPB (National Disaster Management Agency), HIMPERRA (Community House and Settlement Association), affected comunity

User Hub:
TDMRC will encourage, engange, and train the community to collect data and submit it in the platform

User:
- Affected community will get knowledge how to measure flood depth and physical loss due to floods
- Affected community will do the data collecting and submit the data to the platform

Experts:
- Data analysis
- Recommendation for disaster mitigation

- TDMRC will make participatory flood damage assessment training
- KOPHI members will collect data and submit it to the platform, as well as promote our project to the society
- Local government provide the required legal permits and collaboration
- Citizen will collect data and submit it to the platform.

The key partners in this project:

1. Experts on disaster and IT --> they will be involved in conceptualization and planning applications, technical guidance for users, and analyzing data for decision making.
2. Local government and agency --> they will assist in actualizing the project, provide legal permits, and have resources that can be used to support the project.
3. Local NGO --> they will communicate to users to promote and attract people to participate in the project.

1. The increase of extreme rainfall induced by climate change
2. The increase of flood risk induced by high rate of urbanization and urban growth

who else is in the field?

1. PetaBencana.id --> an official crowdsourcing based flood assessment platform in Indonesia. However, it's not specifically aim to assess flood damage
2. Jakarta Pulse Lab --> a mixed method approach, through which it hamesses alternative data sources and advanced data analytics methods to obtain actionable insights and applies human-centered design to ground-truth insights from its data analysis and research, providing evidence to inform policy makers.

1. The current survey method spent lot of money, labor, and time, and the data is not specific and transparent enough
2. The competitor only provide superficial data and not focusing on flood
3. We will provide specific flood data that is actual, free, and holistic

1. Committed community who have a high interest toward urban issue and climate change
2. Flood depth measuring tool
3. People with IT skill

Next steps? Pilots?

1. Developing our prototype to build a simple, easy, and attractive app design
2. Consulting with disaster experts to validate our questionnaire
3. Obtaining legal permission from the government agency (i.e. support letter)

Cost structure? Financial Sustainability? Revenue streams?

We will need fund for these following points:

• App development and maintanance,

• The researcher and expert to analyze the data,

• Staffs to control the data,

• IT supports to maintain the app, and

• Trainers to train the users.

Some of our target funding sources:

• Research grants (TDMRC, KEMENRISTEK, KEMENDIKBUD, University, etc.),

• Direct funding from government institutions (BNPB, KEMENPUPR, etc.),

• Direct funding from the property investors,

• Direct funding from International Organizations (CERN, USAID, etc.), and

• On-site visitation.

How might this go wrong? How might the problem evolve? What are the legal, cultural and other impediments?

• As a crowdsourcing app, this project relies heavily on volunteer participation. Unfortunately, the community trust is really low, and the lazy culture is not supporting this kind of thing. It results in limited data obtained, where it will affect the validity of the model. To solve this, we engage with KOPHI who have strongly motivated members, so the volunteers will be active in collecting the data.
• Communities with poor budget planning skills will be difficult to estimate the cost of renovating their own house accurately. To solve this, we give training for the user; an online training or video could be our best option.
• Although data is available, disaster risk reduction policy formulation may not be effective due to low investment ratio and limited government capacity. Therefore, we will actively lobby the government, including having a focus group discussion with them.

How will i promote adoption?

• Promote with the help of our key partners, especially KOPHI as our user hub. We will also use social media to keep in touch with the volunteers and report them our progress. We understand that people will be more motivated when they know their action results in some changes. 
• We will approach traditional and online news media to distribute the information about our project.

Meaning of our team’s name:
Garuda is a symbol of our country Indonesia
Garuda Savior means a manifestation of our dedication to building Indonesia as a resilient country.
Our team consists of:
1. Ikhwan Amri (Universitas Gadjah Mada)
2. Cut Puan Tiszani Pasya (Universitas Syiah Kuala)
3. Intan Qanita (Universitas Syiah Kuala)
4. Muhammad Iqhrammullah (Universitas Syiah Kuala)
Together with the citizens of Indonesia, we are collaboratively working to solve the flooding issue by generating a depth damage curve (DDC). The crowdsourced data will be collected using an app we created, namely Ina_Flood. We use a multi-partnership approach that includes, research institutions, NGOs, the business sector, and government agencies.

Ina Flood
Make it one step closer to build a resilient city

• Pistrika, A., et al. (2014). Flood depth-damage functions for built environment. Environmental Processes, 1, 553-572.
• Wijayanti, P., et al. (2017). Estimation of river flood damages in Jakarta, Indonesia. Natural Hazards, 86, 1059-1079.

For more information, we have designed a questionnaire in Epicollect5 application. Search: InaFlood_Open Water

The ppt slides can be downloaded here.

This is our one-minute video