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Nicola Greene, Lee Bosher, Mike Smith Water Engineering and Development Centre Loughborough University [email protected]
Seasonal Access to Water in Khagalgaun, Humla District, Nepal
Format of presentation
• Justification for research
• Methodology
• Findings
• Further research
STORY STATI STICS
But what’s the story behind them?
Improved Drinking Water Supply
Nepal 89*% 80**%
Urban: Rural:
2000 94% 81%
2010 93% 88%
1990 96% 74%
Districts Mountain: Hill: Terai:
76% 82% 78% *UNICEF – JMP 2012
**WaterAid - 2011
48%
64% Gov of Nepal
48% WaterAid
“Seasonality is one of the most neglected dimensions of rural poverty”
(Chambers 2009; Devereux & Sabates-Wheeler 2009)
But is it important to consider
seasonality for water
supply?
Drinking Water
Coverage (%)
100
0
64
Time t
Drinking Water
Coverage (%)
100
0
64
Time Review
64+ x
Temporal poverty is frequently analysed, but the trends examined are typically inter-year (i.e. year to year).
Drinking Water
Coverage (%)
0
x
Time (months)
a
b
Intra-annual
variation
Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec
1. ASKED (+ LISTENED) • 90 semi structured interviews with community members
• 9 Focus Group Discussions
• 30 Key Informant Interviews
2. LOOKED • Lived in the area for 9 months
• Observation of behaviour and
infrastructure functionality
• Detailed field notes + diary
Revolutionary Research Method
“I’m actually going to lose my mind” 19/02/12
“Bed bugs make me very very sad” 30/03/12
3. Made a lot of calendars
RAINY
AUTUMN WINTER
SPRING
0
1
2
3
4
5
Water Availability
LOW
HIGH
0
1
2
3
4
5
Water Demand
LOW
HIGH
0
1
2
3
4
5
Surplus/Deficit
0
1
2
3
4
5
Surplus/Deficit
In winter season, people quarrel from early morning to late evening over access to water
(Kha7-M)
SPRING RAINY
WINTER AUTUMN
• Extremely low quantity • Shortages for irrigation
• Very slippery after rain • Landslides sweep tanks away • Sand in water • Many people away
• Very slippery with snow • Hard to climb steep slopes • Pipes/tanks frozen • All animals and people home
• No time to collect water • Tanks block with leaves/debris
Findings
• This study raises issues of
– Best practice data collection in areas with highly seasonal climate
– Data intensive nature of ‘capturing’ seasonality
– Confidence attributed to data from areas with highly seasonal climates
– Degree with which ‘snapshot’ data is relied upon for decision making in allocation and implementation of projects
Other Seasonal Analyses
• Livelihoods
• Institutional calendar
• Health and vectors for disease
• Bathing, clothes washing and hygiene
• Sanitation
