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Day 2 neno kukluric igrac- data processing

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Day 2 neno kukluric igrac- data processing

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Day 2 neno kukluric igrac- data processing

  1. 1. Neno Kukuric - IGRAC Almaty - July 2014 Data Processing & Harmonisation
  2. 2. Structured data Standardised formats: • Digital maps • Tables (excel) • Text Data collection • Paper maps • Paper reports Text, tabular data, images, maps •Digital data Tables, maps, reports Data Processing From ‘raw’ data to consistently structured data
  3. 3. Gobabis Aminius 50,000 20,000 10,000 5,000 2,000 1,000 17°E 18°E 19°E 20°E 21°E 22°E 23°E 24°E 25°E 26°E -22°S -23°S -24°S -25°S -26°S -27°S -28°S Windhoek Stampriet Gochas Aroab Bokspits Hukuntsi Kang Ncojane Tsabong Werda Goodhope Mmabatho Kuruman Vanzylsrus Tosca 450 TDS mg/l From ‘technical’ maps to simplified thematic maps Data Processing
  4. 4. Harmonisation: Formations
  5. 5. Harmonisation: Formations Uzbekistan Kazakhstan ?
  6. 6. Harmonisation: map information 1 TBA 2 Countries • Countries need consensus on delineation of TBA 2 data sets • National data sets may differ in format Harmonised data Transboundary aquifer • Harmonised TBA map, based on national data sets. For example information on Aquifer productivity (Namibia) and Groundwater potential (Botswana)
  7. 7. Harmonisation: agreements on units 0 0.5 1 1.5 2 2.5 10Log (Yield) m3/h 100 90 80 70 60 50 40 30 20 10 0 Probability % Dolomite Kanye Olifantshoek Botswana Basalt SAB (69) (16) (13) 0 0.5 1 1.5 2 2.5 10Log (Yield) m3/h 100 90 80 70 60 50 40 30 20 10 0 Probability % Kalahari SAB Kalahari Botswana (38) (37) Borehole yield m3/hr (Namibia) , l/s (South Africa)
  8. 8. Harmonisation: agreements on classifications Namibia, 1991 South Africa, 2006 Group A Excellent Group B Good Group C Low Health Risk Group D Unsuitable Class I Operational Class II Max allowable for limited duration mg/l mg/l mg/l mg/l mg/l mg/l
  9. 9. Data processing & Harmonisation Harmonisation is about developing a common language and terminology, i.e. agreeing on: • classifications (suitability for water consumption, land use types, water use types, stratigraphy, etc. etc.) • map scale and map projection • areal sub-divisions for reporting (eg report per local municipality or per district?) • units • table formats • report format • additions/modifications to the methodology (eg: Groundwater community management) • …. • ….
  10. 10. Project workflow / tasks 1. Data collection (incl. data entry and digitising of relevant information) 2. Taking stock (which data are available and which not) and fine-tuning of methodology (data & indicators) 3. Structuring of data (data processing) 4. Harmonising data in a consistent way across the aquifer 5. Producing outputs: Indicators, thematic maps, overview tables, illustrative graphs, conceptual model, assessment report
  11. 11. 11 Thank you

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