Modeling for Watershed Management : A Practitioner's Guide
Watershed management problems are usually quite diverse, and involve a wide range of biological, geological, chemical, and physical processes with complex human, social, and economic contexts. The working note seeks to show that computer modeling a...
| Main Authors: | , , |
|---|---|
| Format: | Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2017
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/221531468330977191/Modeling-for-watershed-management-a-practitioners-guide http://hdl.handle.net/10986/27841 |
| Summary: | Watershed management problems are
usually quite diverse, and involve a wide range of
biological, geological, chemical, and physical processes
with complex human, social, and economic contexts. The
working note seeks to show that computer modeling allows us
to better organize, test, and refine our thinking about
watershed management problems and potential solutions.
Typically, the flow of water leads modeling to be organized
into the following areas: (i) precipitation and climate
models; (ii) precipitation-runoff models; (iii) stream and
aquifer models; (iv) infrastructure operations models; (v)
economic, agronomic, social, environmental demand and
performance models; and (vi) decision-making models.
Selecting the right model to apply to specific problems
requires that several factors be considered along with the
objectives for modeling in the context of the field decision
problem. Key factors include understandability, development
and application time, resources required, transferability
and maintenance. Good modeling is common-sense and
understanding reduced to calculation for the purposes of
gaining insights into a real problem. Modeling should aid
discussions, help thinking and provide insights to problems
where individuals and interests struggle to understand the
problem and struggle to work together to address a problem.
To aid model development and the interpretation and
communication of modeling and model results and insights,
simplicity is a great virtue. While complex problems
sometimes require complex models, shedding of unneeded
complexity is important. Local and in-house expertise is
preferred when developing and applying watershed models
because of better familiarity with the problems assessed.
Model integration is a growing trend but requires as much
expertise and resources as development of any single model component. |
|---|