Municipality and System Level Vulnerability, Risk and Resilience Mapping (MULVAR)
Visualization dashboard for the WASH sector
About the project
This two-year (2023–2024) research project titled Addressing climate vulnerability in Nepal through resilient inclusive WASH systems (RES-WASH) is implemented by the International Water Management Institute (IWMI) office in Nepal in collaboration with Bagmati Welfare Society Nepal (BWSN); Global Institute for Interdisciplinary Studies (GIIS); Everest Club, Dailekh; and National Association of Rural Municipalities in Nepal (NARMIN). The project is funded by the Water for Women Fund, a key initiative of the Department of Foreign Affairs and Trade (DFAT) as part of the Australian Aid program.
The RES-WASH project aims to achieve the following objectives:
-
Assess the vulnerability and risk of WASH infrastructure and facilities to climatic and non-climatic hazards such as landslides.
-
Identify gendered and social vulnerabilities related to WASH and climate change experienced by diverse groups of women, girls, PwDs and marginalized communities.
-
Improve knowledge and capacity for effective WASH systems, programs and institutional mechanisms that are more inclusive and climate resilient.
More information about the project can be accessed from: https://reswash.iwmi.org/
About the methodological approach
The risk assessment approach adopted in this study is based on the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). A six-step framework was used for vulnerability and risk assessment at the municipality level. As per the IPCC AR5 risk framework, risk is the function of hazards, vulnerability, and exposure (Das et al., 2020). Vulnerability is calculated as the product of sensitivity and adaptive capacity. In total 183 indicators were selected for the risk assessment (Table 1). To pledge comprehensive, accurate, and relevant data with an appropriate structure, a stringent filtering process was used to standardize the indicators. A multicollinearity test was independently conducted on variables within sensitivity, exposure, adaptive capacity, and hazard categories to address potential collinearity issues. This reduced the number of indicators to 118 for Dailekh and 119 for Sarlahi (Table 1). The selected indicators are indicated in bold and italics. The dashboard, however, displays all indicators as they provide valuable information to our local partners and aid in the planning and action plans for the districts.
Data used in the dashboard and their sources
| Hazards | Sensitivity | Adaptive capacity | Exposure |
|---|---|---|---|
| Incidences, damages and deaths by Landslide, Flood, Hailstorm, heatwave, coldwave, windstorms1,2, lightning, fire, | Census Data | Census Data | Census data6, WASH related disease incidences |
| Incidences of Forest Fire3, air pollution area, | Elevation | WASH related disease | |
| Climate data | WASH related disease incidences | Social, demographic, financial, institutional data related to population in 2021 |
| S.N | Hazard | Sensitivity | Adaptive capacity | Exposure |
|---|---|---|---|---|
| 1 | Total number of flood incidence | Population density | Percentage of economically active population | Total number of male population |
| 2 | Total number of avalanche incidence | Average number of people per household | Percentage of households with household assets | Total number of female population |
| 3 | Total number of landslide incidence | Percentage of religious minority population | Percentage of households with television access | Change in Household number (2011-2021) |
| 4 | Total number of coldwaves incidence | Percentage of absentee population | Percentage of households that are female owned | Population Change (2011-2021) |
| 5 | Total number of heatwaves incidence | Total number of male migrants | Percentage of households with land owned by female | Percentage of population change (2011-2021) |
| 6 | Total number of hailstorm incidence | Total number of physically disabled persons | Percentage of population who only completed school leaving certificate (SLC) | Total number of acute gastro-enteritis (age) cases |
| 7 | Total number of windstorm incidence | Total number of adolescent population (10-19 years) | Percentage of population who completed college degree | Total number of ameobic dysentery/amoebiasis cases |
| 8 | Total number of lightning incidence | Percentage of population < 5 years | Percentage of employed in transportation, communication, and other public utilities | Total number of bacillary dysentery/shigellosis cases |
| 9 | Total number of fire incidence | Total number of infants (vulnerable group) | Percentage of employed in accommodation and food services | Total number of bacterial intestinal infection cases |
| 10 | Total number of household damaged by flood | Total number of women of reproductive age (15-45 years) (vulnerable group) | Percentage of employed in public administration, defense, and social security | Total number of cholera cases |
| 11 | Total number of household damaged by landslide | Total number of girls and women above age 15 | Percentage of employed in trade and commerce | Total number of hepatitis a cases |
| 12 | Total number of death by avalanche | Total number of girls under age 15 | Percentage of households with access to internet | Total number of hepatitis e cases |
| 13 | Total number of death by landslide | Total number of boys under age 15 | Percentage of households with Cement bonded bricks/ stone foundation | Total number of intestinal worms cases |
| 14 | Total number of death by cold waves | Percentage of female-headed households | Percentage of households with Reinforced Cement Concrete with pillars foundation | Total number of jaundice cases |
| 15 | Total number of death by heat waves | Percentage of families occupying rented houses | Percentage of households with Tap/piped water (within premises) | Total number of presumed non-infectious diarrhoea cases |
| 16 | Total number of death by fire | Percentage of population who cannot read and write (illiteracy) | Percentage of households with Tubewell / handpump | Total number of typhoid (enteric fever) cases |
| 17 | Total number of death by storms | Percentage of employed in agriculture, forestry, fishing, mining, and quarrying | Percentage of households with Covered well/kuwa | Total number of volume depletion (dehydration) cases |
| 18 | Air Pollution Area | Percentage of employed in manufacturing and construction | Percentage of households with Jar / bottle | Total number of neonatal conjunctivitis |
| 19 | Total sum of number of icing days (ID) | Percentage of households without access to communication and transportation means (no amenities) | Percentage of households with Electricity lighting | Total number of conjunctivitis cases |
| 20 | Total sum of number of frost days (FD) | Percentage of households without electricity | Percentage of households with Solar lighting | Total number of japanese encephalitis cases |
| 21 | Total number of consecutive dry days (CDD), Maximum length of dry spell, maximum number of consecutive days with RR < 1mm | Percentage of population without access to (improved) sanitation (e.g., Toilet) | Percentage of households with Bio gas lighting | Total number of scrub typhus |
| 22 | Total sum of cwd, Maximum length of wet spell: maximum number of consecutive days with RR ≥ 1mm | Percentage of households that use firewood as fuel source | Municipality with Clean and Healthy Living Behaviour program (PHBS) | Total number of acute encephalitis like syndrome (aes) cases |
| 23 | Total number of days with extremely very wet days R99pTOT | Percentage of households with Mud bonded bricks/ stone foundation | Number of water purification services | Total number of clinical malaria cases |
| 24 | Total number of days with very wet days R95pTOT | Percentage of households with Wooden pillars foundation | Municipality with a specific WASH action plan | Total number of dengue fever cases |
| 25 | Warm spell duration indicator (WSDI), Annual count of days with at least 6 consecutive days when TX > 90th percentile | Percentage of households with Other foundation | Municipality with a specific disaster action plan | Total number of filariasis cases |
| 26 | Cold spell duration indicator (CSDI), Cold speel duration index: Annual count of days with at least 6 consecutive days when TN < 10th percentile | Percentage of households with Tap/piped water (outside premises) | Total number of kala-azar/leshmaniasis cases | |
| 27 | Total sum of sdii (Simple precipitation intensity index) | Percentage of households with Uncovered well/kuwa | Total number of malaria (plasmodium mix) | |
| 28 | Total sum of gsl (Growing season length) | Percentage of households with Spout water* | Total number of malaria (plasmodium falciparum) cases | |
| 29 | Total sum of r10mm (Annual count of days when PRCP ≥ 10mm) | Percentage of households with River /stream | Total number of malaria (plasmodium vivax) cases | |
| 30 | Total number of days very heavy rain days (R20m) | Percentage of households with Other Drinking Water | Total number of acute flaccid paralysis (afp) cases | |
| 31 | Total number of annual total wet-day PR (PRECTOT) | Percentage of households with Kerosene lighting | Total number of anaemia/polyneuropathy cases | |
| 32 | Total sum of tx10p (Percentage of days when TX < 10th percentile) | Percentage of households with Other lighting | Total number of avitaminoses & other nutrient deficiency cases | |
| 33 | Total number of days with TX greater than 90th percentage (50th percentage) | Total expected live birth | Standard deviation of slope | |
| 34 | Total number of monthly maximum value of daily maximum temperature (hot days) | Total expected pregnancies | Standard deviation of elevation | |
| 35 | Total sum of tn90p (Percentage of days when TN > 90th percentile) | Median Slope | Percentage of vegetation coverage | |
| 36 | Total number of Monthly maximum value of daily minimum temperature (hot nights) | Median Elevation | ||
| 37 | Total sum of TNn (Minimum value of daily minimum temperature, cold nights) | Total burnt area (2000-2022) | ||
| 38 | Total sum of tnx (Maximum value of daily minimum temperature, hot nights) | Sex ratio (male: 100 females) | ||
| 39 | Total sum of dtr (Daily temperature range) | Percentage deforested area (2000-2022) | ||
| 40 | Total sum of rx1day (Maximum 1-day precipitation) | Percentage agriculture land area based on 2019 LULC map | ||
| 41 | Monthly maximum consecutive 5-day precipitation (Rx5day) | Distance-Physical Remoteness in Nepal | ||
| 42 | Slope sum of number of icing days (ID) | Access to roads (number of people in palika per road kilometer) | ||
| 43 | Slope sum of number of frost days (FD) | Percentage of Dalit population | ||
| 44 | Slope number of consecutive dry days (CDD), Maximum length of dry spell, maximum number of consecutive days with RR < 1mm | Percentage of household population with E. coli in household drinking water | ||
| 45 | Slope sum of cwd, Maximum length of wet spell: maximum number of consecutive days with RR ≥ 1mm | Percentage of poor households | ||
| 46 | Slope number of days with extremely very wet days R99pTOT | Water fetching duration over 3 hours | ||
| 47 | Slope number of days with very wet days R95pTOT | Water fetching duration between 1-3 hours | ||
| 48 | Slope Warm spell duration indicator (WSDI), Annual count of days with at least 6 consecutive days when TX > 90th percentile | Water schemes need major repair | ||
| 49 | Slope Cold spell duration indicator (CSDI), Cold speel duration index: Annual count of days with at least 6 consecutive days when TN < 10th percentile | Water schemes need rehabilitation | ||
| 50 | Slope sum of sdii (Simple precipitation intensity index) | Amount of tariff collected by water supply scheme in rupees | ||
| 51 | Slope sum of gsl (Growing season length) | Number of households using beach/chlorine as water treatment | ||
| 52 | Slope sum of r10mm (Annual count of days when PRCP ≥ 10mm) | Number of households using water treatment as - Use a water filter | ||
| 53 | Slope number of days very heay rain days (R20m) | Number of households using solar disinfection as water treatment | ||
| 54 | Slope number of annual Slope wet-day PR (PRECTOT) | Number of households with rainwater harvesting | ||
| 55 | Slope sum of tx10p (Percentage of days when TX < 10th percentile) | Number of schemes with Water Users and Sanitation Committee registered | ||
| 56 | Slope number of days with TX greater than 90th percentage (50th percentage) | Number of schemes with Water Supply and Sanitation Technician | ||
| 57 | Slope number of monthly maximum value of daily maximum temperature (hot days) | Percentage of indigenous population | ||
| 58 | Slope sum of tn90p (Percentage of days when TN > 90th percentile) | |||
| 59 | Slope number of Monthly maximum value of daily minimum temperature (hot nights) | |||
| 60 | Slope sum of TNn (Minimum value of daily minimum temperature, cold nights) | |||
| 61 | Slope sum of tnx (Maximum value of daily minimum temperature, hot nights) | |||
| 62 | Slope sum of dtr (Daily temperature range) | |||
| 63 | Slope sum of rx1day (Maximum 1-day precipitation) | |||
| 64 | Slope Monthly maximum consecutive 5-day precipitation (Rx5day) | |||
| 65 | Rate of temperature change | |||
| 66 | Coefficient of variation of precipitation |
Bold and Italics data are used for vulnerability and risk assessment, while the dashboard shows all the indicators.
Data Source:
-
DesInventar Sendai (https://www.desinventar.net/)
-
Bipad portal ( https://bipadportal.gov.np/ )
-
MODIS Active Fire Detections (doi:10.5067/FIRMS/MODIS/MCD14DL.NRT.006)
-
ECMWF Reanalysis v5 (ERA5) https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5
-
Elevation Digital Elevation Model, Shuttle Radar Topography Mission (SRTM) https://doi.org/10.5069/G9445JDF
-
National Statistics Office (2023). National Population and Housing Census 2021. National Report
-
Integrated Health Management Information System (IHMIS) Government of Nepal, Ministry of Health and Population https://dohs.gov.np/information-systems/health-management-information-section/ Das, S., Ghosh, A., Hazra, S., Ghosh, T., de Campos, R. S., & Samanta, S. (2020). Linking IPCC AR4 & AR5 frameworks for assessing vulnerability and risk to climate change in the Indian Bengal Delta. Progress in Disaster Science, 7, 100110.