GIS can model and map various impacts of climate change. It can model CO2 emission sources and storage, map solar potential on rooftops, analyze impacts on forest cover and vegetation over time using satellite data, project impacts on agriculture like changes in crop yields and help determine best farming practices, map species vulnerability and help with conservation efforts, model impacts on water bodies like changes in water yield and flooding/drought risks, map climate zones based on vulnerability parameters, and help predict future temperature changes based on statistical analysis of past weather data. GIS is a useful tool for understanding, projecting, and responding to various effects of climate change.

1. GIS And Climate Change

2. What is climate change?
• Climate change is a long-term shift in weather conditions identified by:
– changes in temperature,
– changes in precipitation,
– changes in winds, and other indicators.
• Any factor that causes a sustained change to the amount of incoming energy
or the amount of outgoing energy can lead to climate change.
• Natural factors –
– volcanic activity, changes in solar radiation.
• Human causes –
– burning of fossil fuels, conversion of land for forestry and agriculture,

3. Why we’re concerned?
• Warming of 2○ C or more can cause:
– abrupt monsoon changes,
– leading to more frequent droughts and floods.
• At 2.5°C warming:
– melting glaciers over the Himalayas,
– Affecting the flow pattern of Indus, Ganges, and Brahmaputra rivers,
– Also severely impacting agriculture, hydropower.
• Coral bleaching , frequency is projected to increase.
• Presently about 27000 species become extinct every year.
• By 2050, about 30% species are expected to extinct.

4. GIS modeling of CO2 emission sources
and storage possibilities
Source: Sahzabi et. al, 2011
Modeling CO2 dispersion
on the surrounding
environment
Transportation
of
CO
2
to
sink
Importing output to
ArcGIS, to get
dispersion map
Define C risk zones
Selection of CO2
sources
Mapping of C sink

5. Mapping solar potential of rooftop
Identification of rooftop
area
ArcGIS tool - inclination, orientation, and
clouding
Calculation of solar
potential
solar suitability, potential power output, CO2
reduction calculation

6. Climate change impact on forest cover
and vegetation
Source: Palmate et. al, 2014
Satellite data
Meteorological
data
NDVI method
Supervised
classification
rainfall
temperature
Vegetation Forest cover Seasonal avg
Establishment of relationship

7. Agriculture and Climate Change
• The agricultural sector represents 35% of India’s Gross National Product (GNP)
• The impact of climate change on agriculture could result in problems with food security and
may threaten the livelihood activities upon which much of the population depends.
• Climate change can affect crop yields (both positively and negatively).
• GIS is helpful in projecting current and future fluctuations in precipitation, temperature,
crop output, helpful in creating farming techniques.
• GIS can analyze soil data combined with historical farming practices to determine the best
crops to plant.
• Mapping crop yield deviation with climate change, can provide solutions (like crop
diversification) for increasing crop yield.

8. Climate change impact on biodiversity
• Climate change –increase vulnerability of species leading to loss and extinction.
• Data on species and habitat distribution from different dates allow monitoring of
the location and the extent of change.
• Mapping species vulnerability with meteorological parameters, can provide better
understanding and accordingly actions can be taken (like reallocation of
vulnerable species).

9. Impact of climate change on water
bodies
Modelling of river basin using
SWAT (soil and water
assessment tool)
Simulated Meteorological
data (PRECIS model)
• Determination of water yield, evapotranspiration
• Prediction of floods, droughts can be done.
• Their consequences on agriculture can also be
studied

10. Climate Zones Mapping
• Define Parameters
• Giving weights to those parameters according to their impact .
• Establishment of a single parameter defining the vulnerability of climate
change using statistical analysis
• Defining climate vulnerable zones.

11. Future temperature prediction
• Establishing empirical relationship from the past records.
• Statistical analysis of the meteorological data.
• Temperature zone mapping