Rural Resilience: Flood management for rural areas

2021 was a disastrous year, apart from the rise of covid cases and the lockdown being irregular, the world saw the second highest number of floods ever recorded- 222 just behind the 226 recorded in 2006. In rural India, the case is worse, where floods claim almost 12% of the landmass annually; they're a horrific reality that rips people apart. Thousands of people drown in flooding each year, and millions more are forced to flee their homes, their possessions, and the entire basis of their existence. Floods are responsible for 63% of property damage and 32% of deaths in India connected to natural disasters.

Though I have been born and brought up in a state known for housing the 18th biggest desert in the world- Thar and floods being very uncommon in my city, having my father working in the waterworks industry gave me a lot of insights into disasters caused by waters. I have a very curious personality and hence keep asking my parents regularly for new information related to their respective work fields. My father once told me about one of his friends who lived in Bihar and the flood condition in Bihar is very bad due to the lack of management. After extensive research I found out that the overflowing of one specific river Kosi- which is a tributary of the Ganga river- damaged approximately 20,000 km² of agricultural land annually, which caused a huge blow to the rural economy given that 80% of Bihar’s population is agriculturally employed. Hence, my aim was set- to contribute to the management of the floods in Bihar.

The research project develops a novel strategy for managing floods in rural regions, focusing on a mathematical model which outputs a drainage system design. Our project sets the drainage system as the primary output parameter, in contrast to standard approaches that focus on flood prediction, representing an advancement in flood management tactics. The study, which concentrated on Bihar's flood-prone Supaul area, gathered crucial information for regression analysis, including rainfall intensity, land use, and soil types. This resulted in the development of a relationship model that forecasts the likelihood of flooding. Then, taking into consideration the size of the catchment and the runoff coefficients based on land use, linear programming was used to maximise the amount of floodwater directed into the drainage system. An adaptable mathematical model was developed as part of the research and customised to the special features of the Supaul region, providing a model for other flood-prone locations. The research also suggested basin size suggestions that were tailored to the local environment, further improving drainage system effectiveness.The model produces a set of equations that requires little input data and determines the best drainage system design. Due to its adaptability, it may be used in various districts, which makes it a useful tool for municipalities. With potential implications in flood-prone areas across the world, this discovery offers a substantial development in flood management strategies.

Flood control in rural regions is a subject that our research effort directly addresses.  With a particular emphasis on Supaul, a district in Bihar, India that experiences flooding often, the project's conclusions will be crucial for practical implementation and a major boost to the local economy. The key to the answer is a cutting-edge mathematical model that maximises the design of drainage systems according to regional variables including soil type, land use, and rainfall intensity.

The project's primary stakeholders are the local government officials and the people who live in rural areas that are prone to flooding. Seasonal floods have caused many challenges for the locals lately, including fatalities, house displacement, and interruption of livelihoods. Moreover, floods seriously harm infrastructure and property, and in areas such as Bihar where agriculture is the primary industry, yearly flooding destroys large tracts of fields, affecting livelihoods and food security.

The mathematical model gives local government representatives more influence by offering a useful instrument for designing drainage systems. The program helps towns plan and carry out efficient flood control measures by suggesting the best drainage systems based on local data. This might result in a major decrease in the amount of infrastructure and property damage caused by flooding, which would save money losses for both local governments and citizens. Furthermore, by empowering local governments to actively control flood risks, effective drainage systems can enhance disaster preparedness by perhaps reducing fatalities and displacement during flood disasters.

The project's influence goes beyond Supaul's residents. The mathematical model's flexibility enables it to be tailored to diverse rural locations with distinct flood patterns. This offers a repeatable and data-driven method for reducing flood risks and enhancing lives, which might benefit people living in flood-prone areas all around the world. The results of the study may also be used by disaster management organisations and policymakers to develop more comprehensive flood control plans and strategies at the local, state, and federal levels.

Summing up, this study effort provides a major improvement in rural flood control. The solution possesses the capacity to significantly enhance lives, livelihoods, and readiness for disasters on a local and perhaps global level by providing towns and citizens with the necessary tools through its inventive approach.

As I originate from Rajasthan, India, a state known for its arid climate, my interest in flood management may appear unconventional. But this passion is the result of a special familial dynamic. I have a strong grasp of water resource management and its complex issues surrounding flooding due to my mother's town planning experience and my father's career in waterworks. Their priceless first-hand knowledge has given me a clear understanding of the actual effects of flooding on areas that are already vulnerable. My academic goals and my passion for infrastructure management are a natural match. Engineering is a subject that interests me, especially when it comes to sustainability and environmental research. These two shared interests drove a prior effort in which I directed the creation of a regional system for detecting poor air quality. My abilities in data analysis and project management, which are essential for the accomplishment of this flood management campaign, have been clearly refined by this endeavour.

India's news media often present a horrifying image of the destruction wrought by floods. These accounts emphasise the staggering death toll, destruction of property, and interruption of livelihoods. Observing this continual battle has stoked my intense desire to help find a way to lessen this misery.
Overall, I believe that I'm well-positioned to take on this challenge because of my history. My scholastic endeavours have helped me to develop a strong grasp of the technical facets of water management. Moreover, the combination of my project management abilities and my parents' practical expertise builds a solid foundation for success.

I have chosen the concept stage as the basic model has been created but there are a lot of additions that need to be made to make the model better. The future additions will seek to develop new flood management strategies that involve supplementing and changing existing drainage systems to reduce costs and creating a network of channels. The model, right now, is able to produce a single channel and will be upgraded to be able to output a network of drainage channels. 

I'm applying to Solve because I believe that the knowledge and resources of the program would greatly increase the effect of my project to control floods in rural regions, with a specific focus on Supaul, a district in Bihar, India that is prone to flooding. With Solve's assistance, I will be able to conquer these three major obstacles:

• Technical expertise: The design of the drainage system in my project is based on a mathematical model. Although the fundamental idea is proven, working with Solve's network of data scientists and engineers may greatly improve the precision and efficacy of the model. Their knowledge can assist in improving the model's algorithms to make sure it takes into account all important elements unique to the local context.

• Scaling and Replication: This project's ultimate objective is to function as a repeatable model for flood control in other rural communities. I can connect with stakeholders in other flood-prone areas using Solve's network and resources, facilitating knowledge transfer and the model's adaption to other circumstances.

• Sustainability and Environmental Impact:  While flood mitigation is the primary objective, ensuring the project's long-term sustainability and minimal environmental impact is crucial.  Solve's network of sustainability experts can provide valuable guidance on selecting eco-friendly materials for drainage systems and exploring renewable energy sources to power them, if applicable.  This focus on sustainability aligns with Solve's mission and strengthens the project's overall impact

• Data Acquisition and Analysis:  The mathematical model at the project's core relies on robust data on factors like rainfall patterns, soil types, and land use.  Solve's network can connect me with researchers and data scientists who can assist in acquiring high-quality, localised data specific to Supaul.  Additionally, their expertise in data analysis can help identify hidden trends and optimise the model's accuracy in predicting flood risks.

By addressing these crucial areas, Solve's support can significantly enhance the project's effectiveness and long-term impact.  The project will not only protect lives and property in Supaul but also establish a replicable model for broader implementation, fostering resilience in communities across the globe.

The research project develops a novel strategy for managing floods in rural regions, focusing on the development of a thorough mathematical model along with a successful drainage system design. Our invention sets the drainage system as the primary output parameter, tasked with rapidly clearing floods from the afflicted area, in contrast to standard approaches that largely focus on flood prediction. With a focus on practical, on-the-ground measures, this change represents a significant advancement in flood management tactics. 
The creation of a flexible mathematical model adapted to the unique needs of the rural region under study is the basis of this invention. This model not only takes into account the special features of the region but also provides a guide for adoption in other flood-prone areas. This flexibility recognizes the various topographical and infrastructure characteristics of regions dealing with comparable problems. Our study provides towns and agencies involved in flood control with a powerful tool for making quick and informed choices by providing a scalable and transferable model. 
The project also adds a unique aspect by offering basin size suggestions that are tailored to the regional environment. This component is essential for optimising the functionality and efficiency of the drainage system design. Municipal authorities can be given a useful guideline by tailoring basin sizes to the unique characteristics of the rural region, which can improve their capacity to proactively reduce flood risks.

This project directly addresses the challenge of flooding in rural areas by using a mathematical model to design optimal drainage systems. By collecting data on factors like rainfall and soil types, the model can predict flood risks and recommend the most effective drainage solutions for a specific location. This leads to improved drainage infrastructure that can handle larger volumes of floodwater, ultimately reducing flood damage to homes, farms, and critical infrastructure. The project's long-term impact goes beyond immediate flood mitigation. The data collected and the model itself can be continuously refined, creating a powerful tool for future planning and development. Additionally, the success of this project can serve as a blueprint for other flood-prone regions. By openly sharing the model and lessons learned, we can empower communities worldwide to take proactive measures against flooding. This fosters a ripple effect of resilience, ensuring long-term safety, security, and a more stable future for countless people living under the threat of floods.

This project has two main impact goals that aim to significantly improve the lives of people in Supaul and beyond. Firstly, I aim to demonstrably reduce flood damage, targeting a specific decrease in flooded land area. This translates directly to safer homes and communities, with fewer possessions lost and less disruption to daily life. We'll track progress by comparing pre- and post-implementation data on flood events. Secondly, the project seeks to empower other regions by making the mathematical model and resources openly available. By measuring downloads and inquiries from other flood-prone communities interested in adapting the model, I can gauge the project's potential to create a ripple effect of resilience across the globe.

Linear programming is a mathematical technique for maximising or minimising a linear function of several variables, for this project, the variable maximised was the flooded water sent to the drainage system. First, it was necessary to determine which area I will be working around to generalise the model, hence I chose Supaul district in Bihar, a city highly prone to floods due to the Kosi river. Next, I had to find other important information such as the rainfall intensity, land usage and soil types in order to be able to form necessary equations and perform the regression analysis to make a relationship model. The model then told us the probability of the flood in the district. 
This information was then further used to create the objective function and constraint equation. The objective function, as mentioned earlier, was to maximise the amount of flooded water that went to the drainage systems. While creating the constraint equations, multiple parameters were taken into consideration such as the basin size and the runoff coefficients based on the different types of land usage in the district. These parameters were important for creating the constraint equation as they helped in approximately determining what amount of water would be in excess after the flood. Then a linear programming approach was used to give the most efficient design for the drainage system.

This is an individual project.

I have been working on this project since September 2023. Hence, it has been 8 months since I started on this project.

This is an individual project, but I believe that I am myself diverse. Volunteering for international organisations and community activities, I have grown to embrace my varied experiences. Ranging from interacting with people globally to appreciate differences to doing classical dance to stay connected to my roots, I believe intercultural diversity helps me find a balance between modern and traditional values. To be able to do this, one needs to be both a good listener and communicator. This allows me to effectively voice and understand different opinions. Moreover, values play an important role in someone’s life and are a factor in shaping identity and motivating action. Hence, I respect other people’s values. I hope to encourage others to be  engaged in conversation, while presenting their own ideas. These two ways, I believe, will enable me to make the camp more inclusive and inviting for everyone.