World Aquifer Forecasting Engine and Research

The rapid depletion of underground water reservoirs throughout the country is the biggest environmental challenge that Pakistan is currently facing. This problem if not addressed could lead to life-threatening conditions across the densely populated Indus Plain. In our project, we are trying

Project Title

World Aquifer Forecasting Engine and Research

Project Area of Specialization

Computer Science

Project Summary

The rapid depletion of underground water reservoirs throughout the country is the biggest environmental challenge that Pakistan is currently facing. This problem if not addressed could lead to life-threatening conditions across the densely populated Indus Plain.

In our project, we are trying to build a forecasting engine that can analyze the historical data to classify the variables that are the main causes of this problem. Moreover, the engine will make (decades into the) future forecasts (predictions) of the underground water table in areas of choice anywhere on the planet. Multiple forecasts will be made with the help of statistical (ML) techniques using a combination of variables. Why? because forecasts with different combinations of variables will allow us to assess the effectiveness of solutions that public or private agencies have proposed. Questions like "How will the water table change if the city keeps expanding at the current rate but the deforestation and temperatures keep rising?"

To build this forecasting engine, we will need to train machine learning models on past data of regions of choice. Data on variables like Water Level, Population, City Expansion, Temperature, Deforestation, Precipitation, and more will be needed.

Project Objectives

Our objective is to build a forecasting engine that can analyze the historical data to classify the variables that are the main causes of this problem. Moreover, the engine will make (decades into the) future forecasts (predictions) of the underground water table in areas of choice anywhere on the planet. Multiple forecasts will be made with the help of statistical (ML) techniques using a combination of variables. Why? because forecasts with different combinations of variables will allow us to assess the effectiveness of solutions that public or private agencies have proposed. Questions like "How will the water table change if the city keeps expanding at the current rate but the deforestation and temperatures keep rising?"

Project Implementation Method

By collecting, analyzing, and processing historical data. We will get statistical insights into different variables that might or might not have any relation with underground water level. With this we will set up multiple data sets with different variables and use them to train machine learning models that can make underground water level forecasts for that region. In current iteration, Islamabad is our target region. 

Benefits of the Project

1- The outcomes of our project will be the only ones of their kind. There is not a single product for Pakistan that provides Public Geographical Visualizations of the underground water reservoirs. Our findings will help researchers to further their understanding of the problem under study.

2- Since all of our results will made public, everybody will be able to access it. Presently, relevant data is either not public or is very difficult to access and understand because of its complex scientific nature.

3- We will deploy all of the processed data in a centralized repository and encourage our Universities students and others to use it to expand the research on the problem.

4- The project outcomes, Government will be able to devise better and effective policies to tackle the problem. This will reduce wastage of funds and allow authorities to divert the spending towards other issues.

5- Our project might help us avoid the looming catastrophe of extensive water shortage.

6- It will set precedent for students like us and the Government to expand study on the problem that has been ignored for so long.

Technical Details of Final Deliverable

Our final deliverable will a command line or web-app based forecasting engine that can make predictions such predictions and give critical insight into the underground water level of a specified region.

Users will have to select a specified region, collect appropriate data from relevant sources, provide a source to that data, and the forecasting engine will process it and make the predictions.

Final Deliverable of the Project

Software System

Core Industry

Others

Other Industries

Core Technology

Others

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People, Clean Water and Sanitation, Sustainable Cities and Communities, Responsible Consumption and Production, Climate Action, Life on Land, Partnerships to achieve the Goal

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com