Environmental Engineering Reference
In-Depth Information
Sub -
elds for Component 5: Functionality of national/regional databases
(a) National level : Trend analysis emerging from sector speci
c or pilot projects
in emerging and developing countries
(b) Regional level : Establishment of a nexus index that can potentially inform
decisions on allocation of
financial and/or human resources by governments/
donors at different scales: Regional, national and provincial for integrated
management of environmental resources
International level : Donor harmonization, cross-fertilization across regions/
countries, institutional arrangements for establishment and maintenance of a
global nexus index
4.3 Science Domain: Nexus Observatory Classi
Expected Outcomes
1. Boundary conditions: Speci
ed to determine applicability of research outputs
2. Scale conditions: Speci
ed to determine applicability of research outputs
3. Intersections: Critical nodes at intersection of biophysical, institutional and
socio-economic domains that
impact upon management of environmental
4. Interactions: Biophysical and institutional processes that impact upon man-
agement of environmental resources mapped
5. Feedback loops: Mechanisms that transmit the effects of policy/programme
interventions on human behaviour and their consequences for resource use
resources identi
Sub -
elds for Component 1: Speci
cation of boundary conditions
(a) Projects and programmes : Analysis of success and failure of policy, pro-
grammes and projects, exploring both backward and forward linkages in an
institutional and biophysical context; clarifying boundary conditions both
spatially and temporally
(b) Linked databases : Analysis of backend data from universities and UN agen-
cies relevant to water resources, systems and flux, waste management and soils
(c) Process documentation : Analysis of regional consultations that generates
important insights relating to needs assessments, gap analysis and overlaps in
a cost-effective manner
(d) Citizen observatories : Employ private data sets based on information from
GIS, mobile and open source computing applications
(e) Data visualization : Employ suitable modelling techniques for data rich and
poor environments
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