Environmental Engineering Reference
In-Depth Information
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elds for Component 2: Speci cation of scale 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 government ministries,
UNU, universities and UN agencies that is relevant to water resources, sys-
tems and flux, waste management and soils
(c) Process documentation : Analysis of regional consultations that generates
important insights related 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/remote sensing techniques for
data rich and poor environments
elds for Component 3: Intersections
(a) Biophysical processes : Employ suitable modelling/remote sensing techniques
for data rich and poor environments
(b) Financing processes : Understanding of norms for allocation of funds, func-
tions and functionaries and transfers, taxes and tariffs
(c) Socio-economic processes: Understanding of demographics, income, ethnic,
gender and resource use attributes of users of environmental resources
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elds for Component 4: Interactions
(a) Donor level : Understanding of donor policies, projects and programmes
(b) National level : Understanding of legal framework, policies and programmes
(c) Provincial
level : Understanding of management strategies, directives and
(d) Local government level : Understanding of equity norms, coordination norms
and allocation norms
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elds for Component 5: Feedback loops
financing structures
(b) Environmental resource : Trends in use of water, waste and soil resources
(c) Human-Environment interaction : (1) Data proxies for environmental resource
flows and fluxes, soil quality and waste characteristics and economic effects of
waste, (2) Data proxies for socio-economic attributes relating to income,
employment, demography, gender and/or ethnicity, and (3) Data proxies for
dimensions of environmental resource use: consumption, price, volumes,
cropping intensity, farming techniques
(d) Programme : Assumptions, risks, outcomes and impact
(e) Project : Assumptions, risks, outputs and outcomes
Interventions : Policy, programme and
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