Finding the most efficient solutions for water resource management using IBM Watson Analytics.

1. Water Resource Management
IBM Watson Analytics
Arun Prasad
Gaurav Pandey
Mrunmayee Shukla
Georgia State University

2. Introduction
• 85% percent of the population lives in driest half of the planet.
• Only 3% of total water is fresh water and two-thirds of that is in the form of frozen glaciers.
Population vs Water availability:
• 1.1 billion people around the world lack access to water
• 2.7 billion face water scarcity during at least one month of the year.
Impacts of Water Scarcity:
What could this mean?
• By 2025, as per UNO’s projection 1.9 billion people will live in countries or regions with absolute
water scarcity
• Two-thirds of the world’s population could be under stress conditions

3. Objective
• Recent changes in fresh water resources across various locations.
• Impact of the following parameters on water conservation techniques:
• Precipitation
• Temperature
• Per Capita
To examine:
To Design:
• A recommendation system that would provide appropriate and optimal water conservation
solutions.
• Potential users will include:
• Government
• Infrastructure Planners

4. • Worldbank.org
• Global Precipitation data.
• Global temperature data.
• Water.usgs.gov
• Water used in the United States.
• ncdc.noaa.gov
• US Average temperature data..
• US Average precipitation data
• data.worldbank.org/data-catalog
• data.worldbank.org/data-catalog/global-water-costing-study
Timeframe of Analysis:
• 2010 - 2016
Data Sources

5. Insight1: Single solution for extreme temperature regions
IBM Watson’s analysis concluded that
• Areas with both extreme cold and
hot temperature yielded similar
recommendations, for low
precipitation values.
• Water treatment plants were
detected as the most viable
solutions at these locations.

6. Insight 2: What is the most common solution for water resource management?
IBM Watson inferred that:
• Underground Water harvesting to be
the most viable and optimal solution
for most of the countries.
• Underground Water harvesting – The
cheapest water management system.
• Model successfully recommends most
Optimal solution.
• Combined with the previous analysis
we can decipher that most countries
lie in the medium to high precipitation
regions and in medium to high-
temperature regions.

7. Insight 3: What if a country has different climatic regions?
• Countries with varying climatic
regions may needs to be analyzed
further.
• US has different temperature and
precipitation throughout.
• Data of all states gave much better
results.
• Other such country may include
India.

8. Insight 3: Contd..
• Underground Water Harvesting is
the most prominent solution for
US.
• The combined model
recommended Dams, as the
solution for US.
• Most of the big dams in west
coast are dried up.
• This shows Underground Water
Harvesting is better solution than
Dams.

9. Insight 4: Social Media Analysis [Twitter]
The Watson Twitter analysis helped us:
• Starting from the year 2016, a
sentiment analysis of Twitter feeds
related to water conservation.
• Water harvesting reveals that not
many people are talking about the
issues related to water scarcity.
• It suggests that there is a lack of
awareness among people related to
the threat of water shortages.

10. Insight 5: Feasibility
A feasibility study by considering the per
capita income of countries was
performed in Watson, that helped us
determine:
• What are the countries lying in 1st
quartiles (low per capita income)?
• For how many such countries Dams is
the recommended solution?
• Since Dams require huge capital, such
solution may not be feasible for these
countries.
• Watson may be trained to provide
much such insights by providing more
parameters.

11. Insights Dashboard:

12. Predictions Dashboard:

13. • This model and insights can be used by any country to find out most efficient water conservation
method based on the climatic conditions.
• Help countries take informed decisions to select most optimal technique for water resource
management.
• Countries with varied climates can extend this model for getting a better solution.
• Sharing resources and technologies to help underdeveloped countries implement recommended
solutions.
• Assess feasibility of recommended solution before starting implementation.
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