Human impact: Socio-hydrology

6 important questions on Human impact: Socio-hydrology

Min 22: the pendula swing

30s-80s: steep increase in population
after 80s: people moved to downward direction of the river basin or out of the basin completely

What is historical socio-hydrology and ....?

  • Coupled human-water-agricultural systems from ancient civilizations and played around
  • Data availability: climate, harvest, agricultural data, etc.
  • Changes in climate or overshoot lead to collapse of civilizations


Maya () and Roman case (virtual water trade)

What is the central Q and 3 failure mechanisms in comparative socio-hydrology

Central Q: What can we learn from comparing these sytems?

Srinivasan et al: Found key similarities within systems that lead to collapse -

3 characteristic failure mechanisms:
  • Unsustainability: overexploitation for irrigation/DW/etc
  • Vulnerability: climate variability (eg extremes)
  • Chronic scarcity: nothing there anymore...
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Link the correct graph to the correct type of comparative socio-hydrology

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How to model socio-hydrological approaches

2 kinds:
  • conceptual models (closer to traditional hydrogeological models, couple equations that you force with data)
    • Toy models: previous slide, investigate what is happening/play around
    • Conceputal models: mimic existing systems, e.g. Maya systems or roman empire
  • Agent based modeling
    • Probabilistic human decision-making (putting sense of intuition into probabilistic model, where agent is precip, people, water, etc)
    • Reacts to other agents and.... (see sldie)

New data and smart modeling are used to model socio-hydrologically. Explain new data and smart modeling and give an example of Tim's reserach on both?

  • Need for unconventional data, e.g.
    • Crop production, global food prices
    • Population and demographics
    • Norms and values, policy (e.g. Historical records such as dams, interventions)
  • Smart modeling: see min 78


New data example: analyzed newspapers for expression of 'env awareness': using language analyses tools to construct quantitative metric. See again min 77 maybee (not highly necessary).

Smart modeling: predicting the ungauged basin. Min 86: Model was validated based on local information. ...

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