Water Resources Management From Hydrology to Yield

1. FETWATER Pilot Training 20 - 24 August 2018 Water Resources Management From Hydrology to Yield

2. Contents Hydrological Cycle Rainfall Streamflow Catchment Developments Evaporation Stochastic hydrology Yield

3. 1. The Hydrological Cycle

4. Understanding catchments

5. Understanding catchments

6. Understanding catchments

7. Understanding catchments

8. 2. Rainfall

9. One can not do water resources Management without Rainfall data Number of useable rainfall stations open over time

11. Why do we need rainfall data? • Water resource, source of streamflow / groundwater • Can affect requirements eg. Irrigation • Intensity eg. flood management • Early warning eg. Drought cycles • Long term cyclic trends, climate change

12. Where to obtain rainfall data from? • DWS Management Framework Rainfall • SAWS: costs • Other • Satellite • Varying time frames: monthly, daily, hourly

13. Collating Rainfall Data • Raw data should be checked • Patched with surrounding rainfall gauges with available data • Individual gauges usually lumped together to obtain representative catchment rainfall

14. 3. Streamflow

15. Number of useable stramflow stations open over time

17. Why do we need streamflow data? • To understand the volume of rainfall that produces surface flows • Natural streamflow data is known as “hydrology” • Yield analyses of water resources requires hydrology • Flow measurements important for operating systems eg. EWR & users’ requirements

18. Where to obtain streamfow data from? Google Earth KMZ file

19. Rainfall-Runoff Relationships • More rainfall = more runoff • Lag can occur • Further material under Pitman Modelling Module

20. Quick Practical • What was the monthly flow out of Jericho Dam in March 1991? • What was the rainfall measured at gauge 0297159W in January 1984?

21. 4. Catchment developments

22. Afforestation Irrigation

23. Urbanisation Alien vegetation Dryland crops Transfers

24. Dams / Reservoirs

25. Why should they be considered? • Often negative impact on streamflow • Quantifying difficult • Changes in flow over time • “Natural Streamflow” required for water resources management assessments

27. Recorded vs natural vs current development level

28. 5. Evaporation

29. Vaal dam surface area when full: 322.75 km2 = 322 750 000 m2 2000 mm = 2 m 2m x 322 750 000 m2 = 645.5 million m3/a Storage of Vaal Dam = 2610 million m3 therefore 25%

30. Required for • Surface water evaporation losses from Dams, rivers • Crop evapotranspiration in determining crop water requirements Types • Lake • S-Pan • A-Pan • Crop

31. Obtained from • Water Resources studies • Usually constant per year, monthly distribution

32. 6. Stochastic Hydrology

33. What are stochastics? • Alternative to Natural hydrology sequence • Only 1 change: rainfall, not dependant on landuse/catchment development changes • Eg. of Vaal Rainfall Cumulative Avg: 648mm

34. Sequence 1 ? Avg: 648mm Sequence 2 Sequence 3

35. Sequence 1 ? Avg: 648mm Avg: 645mm Sequence 2 Sequence 3 Avg: 665mm Avg: 637mm

36. Why use stochastics? • Eliminates the need to plan according to historic events only • Can provide results in terms of assurance of supply, probability of failure (more later) • Use STOMSA to produce stochastic flow sequences from natural historic sequence

37. 7. Yield and Modelling

38. What is yield? • Available water from a water resource system • Volume of water that can be abstracted over a specific time period • Varying types: • Historic firm • Long term at various assurance levels • Short term

39. Spill Recovery tC Failure Critical period Full Supply Volume (FSV) Storage volume Dead Storage Volume (DSV) Time

40. Definition of Modelling “… a simplified mathematical description of a system or process, used to assist calculations and predictions…” – Oxford English Dictionary

41. Benefits of modelling • Allows representation of real world, subject to various human activities / interventions • Can predict behaviour prior to actual experience • Provides testing environment to assess best options for application in real world • Allows “mistakes” without applying incorrect or inappropriate options • Guides design of corrective measures

42. Limitations of modelling • Cannot capture full complexities of real world • Dependent on assumptions • Data availability • Selection of appropriate model • Difficult to standardise modelling approach • Specialist configuration and interpretation • Small user group • Extensive configuration checking

43. Purpose • Assessment • Resource capability • Resource assurance • Water quality • Impact of interventions • Conservation • Resource development • Impact of management options • Resource operation • System maintenance • Monitoring of observed behaviour

44. The modelling process • Define objectives • Identify main physical features • Define system network • Select system operating rules • Undertake scenario analysis • Evaluate results • Implement decision

45. Models and utilities • Hydrological and water quality data pre-processors (various) • Data patching utilities (CLASSR, PATCHR) • Rainfall-runoff models (Pitman) • Stochastic streamflow models (STOMSA) • Water quality models (WQT) • Yield analysis models (WRYM) • Planning analysis models (WRPM) • Information management systems (WR-IMS)

46. Undeveloped catchment Runoff Available flow

47. Available flow Average flow Available flow 4035302520151050 Monthly flow volume (million m3) 0 1 2 3 4 5 6 7 8 9 10 Year

48. Abstraction from river Water user Abstraction Runoff Available flow

49. Abstraction capacity Actual supply Actual supply Available flow 4035302520151050 Average flow Monthly flow volume (million m3) 0 1 2 3 4 5 6 7 8 9 10 Year

50. Reservoir Abstraction from reservoir Water user Abstraction Runoff