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An Exploration of Water Poverty in Lao People’s Democratic Republic Marko Kallio ProGIS Seminaari 8 November 2016.

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Presentation on theme: "An Exploration of Water Poverty in Lao People’s Democratic Republic Marko Kallio ProGIS Seminaari 8 November 2016."— Presentation transcript:

1 An Exploration of Water Poverty in Lao People’s Democratic Republic Marko Kallio ProGIS Seminaari 8 November 2016

2 Water Poverty Water is closely linked with majority of UN’s Sustainable Development Goals Jobs, economic growth, global risks… Water poverty: "a lack of access to sufficient and adequate quality water resource for basic needs“ English definition: Not being able to pay one's water bills

3 Laos Poor Rural One of the least developed nations

4 Research questions Are there distinct differences between areas in their water poverty? 2. Are there distinct spatio-temporal differences in water poverty? 3. What are the causes of water poverty in Laos? Do the causes differ across space and seasons?

5 Methods Water Poverty Index WPI Components
Multidimensional composite index Calculated for 8215 villages across the country WPI calculated for dry and wet season separately Analytical weighting of components using PCA WPI Components Resources: water availability (modelled) Access: presence of water infrastructure Capacity: local management capacity Use: water use and dependency of village population Environment: land use, disaster occurrence, soil degradation…

6 Methods Exploratory (spatial) data analysis Spatial data mining
Geographically weighted summary statistics Geographically weighted regression Geographically weighted principal component analysis Spatial clustering Geographical weighting has many options… Simple Gaussian weighting with 400 nearest neighbors

7 Spatial differences in WPI
Water-poor areas Water-rich areas

8 Seasonal difference

9 Seasonal difference in provinces

10 Clusters

11 GWPCA

12 GW Regression

13 Causes of water poverty
Main relative cause is found in Capacity component In the North, Resource availability causes problems Road access! Significant spatial differences Capacity and Use indicators among the 11 most important regression coefficient Use: low score, strong correlation

14 Conclusion Most important outcomes: New research topics:
Single index score not enough (in highly variable climates) Causes of water poverty differ according to season New research topics: Better inclusion of seasonality in to WPI Seasonal water poverty; can one really be worse off water-wise in the wet season…?

15 Thank you. Data and R code available in http://markokallio
Thank you! Data and R code available in and

16 Water availability modelling
Distributed physically based conceptual hydrological model 5kmx5km grid cell Rainfall and temp. interpolated from point observations No dams/reservoirs!!! Mekong mainstream ~


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