Abstract
This project aimed to understand the likely impact of water quality on ecosystem services, including risk to health and food security (crops and fisheries) within a risk-based framework.
Risk = Hazard * Vulnerability
Hazard was derived as likely exposure to pollution, using available data on land cover; industry location ; fertiliser application; irrigation, sewage treatment and population density.
Vulnerability was mapped as mean capital scores using the Sustainable Livelihoods Framework , based on the 2011 census data. We hypothesised that populations with high access to natural capital and low infrastructure (physical capital) will be more susceptible to pollution.
A Bayesian Belief Network was constructed to conceptualise the framework and was informed by literature, data and expert opinion of the study area by the project investigators.
Risk = Hazard * Vulnerability
Hazard was derived as likely exposure to pollution, using available data on land cover; industry location ; fertiliser application; irrigation, sewage treatment and population density.
Vulnerability was mapped as mean capital scores using the Sustainable Livelihoods Framework , based on the 2011 census data. We hypothesised that populations with high access to natural capital and low infrastructure (physical capital) will be more susceptible to pollution.
A Bayesian Belief Network was constructed to conceptualise the framework and was informed by literature, data and expert opinion of the study area by the project investigators.
| Original language | English |
|---|---|
| Pages | 2 |
| Publication status | Published - 2019 |
| Event | 6th Biennial Symposium of the International Society for River Science: Riverine Landscapes as Coupled Socio-ecological Systems - Universität für Bodenkultur Wien, Vienna, Austria Duration: 8 Sept 2019 → 13 Sept 2019 https://amber.international/event/6th-biennial-symposium-of-the-international-society-for-river-science/ |
Conference
| Conference | 6th Biennial Symposium of the International Society for River Science |
|---|---|
| Abbreviated title | isrs2019 |
| Country/Territory | Austria |
| City | Vienna |
| Period | 8/09/19 → 13/09/19 |
| Internet address |
