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Table J11: Runoff equations forthe ACRU runoff regions of NatallKwaZulu (continued).
ACRU HRU HRU tertiary catchment Runoff equation Correlation Number
runoff hydro coefficient in
region logical sample
zone
11 10 VOl B/02/03B/04/05/06/07B MAR = 10,27 x 10 0,00121 MAP 0,941 8
12 6b UllI13B/21/22/23B/30/40 MAR = 7,22 x 10 0,00132 MAP 0,997 7
13 3a VOlA MAR = 37,79 x 10 0,00083 MAP 0,996 5
14 3b U12N03A/07A MAR = 52,57 x 10 0,00072 MAP 0,999 5
15 2b U23A MAR = 20,81 x 10 0,00096 MAP 0,963 26
16 6a U13A MAR = 17,07 x 10 0,00105 MAP 0,950 14
17 2a T51/52 MAR = 12,31 x 10 0,00128 MAP 0,993 17
18 la T41/53/54/55 MAR = 6,56 x 10 0,00156 MAP 0,968 33
19 3d T35 MAR = 4,33 x 100,00164 MAP 0,972 9
20 3c T31 MAR = 3,00 x 10 0,00169 MAP 0,995 9
21 lb T42 MAR = 3,96 x 10 0,00168 MAP 0,997 8
Source: After Schulze, R.E., 1984. An assessment of the surface water resources
of Natal, Natal Town and Regional Planning Commission Report, VOl 63,
Pietermaritzburg, 44 p. and map.
Note:
Correlation coefficients are very high (all r> 0,941 with 10>0,990).
Accordingly, estimates ofthe MAR which are based on the calibrated
Pitman Model simulations generated by the Hydrological Research
Unit (briefly discussed a little later in the chapter), can be assumed
to be realistic.
(ii) HRU tertiary catchment W34 does not exist.
(iii) HRU tertiary catchment T32 was not included in the study by
Schul2e (1984 - above).
(iv) MAP refers to mean annual precipitation.
10.4.1 KwaZulu catchments
The firm Eksteen Van der Wait and Nissen (1990) in an analysis of catchments in
KwaZulu, divided the territory into 12 catchments on a priority basis (Table J12). Each
catchment was given a three-digit number. The first digit indicates position from south
to north - where 1 represents catchments in the south of Kwazulu; 2 represents the