Annex E:
Estimation of Conversion Factors for Curve
Numbers as a consequence of Deforestation
Mekong River Commission Water Utilisation Project Component A:
Development of Basin Modelling Package and Knowledge Base
Annex E: Estimation of Conversion Factors for Curve Numbers as a consequence of Deforestation
1
Introduction
This note sets out a basis for estimating the impacts of deforestation on rainfall-runoff
relationships as modelled in SWAT (it also provides a basis for examining the impacts of
other land use changes as well).
The fundamental parameter reflecting existing land use in the SWAT model is the curve
number CN21. Broadly speaking, the higher the value of CN2, the faster the rainfall runs off
from the catchment. The SWAT manual provides guidance on “standard” values for CN2
based on examination of a wide variety of catchments2. The values are a function of land
cover and soils and are illustrated below.
Table 1: Standard values of CN2
Land use class
AGRF
1
AGRL
2
CMCL
3
DECD
4
EHCD
5
EMLD
6
GRAS
7
MEDM
8
MXMS
9
PLAN
10
WSEV
11
A
62
31
50
45
25
26
49
40
43
45
39
Hydrologic Soil Group
B
C
73
81
59
72
58
62
66
77
55
70
61
77
69
79
66
80
72
88
66
77
61
74
D
84
79
65
83
77
85
84
87
95
83
80
Notes
Agriculture, converted forest land, using wheat as a proxy
Agricutlure, rice areas, based on alfalfa as surrogate
Crop mosaic, cropping area >30%
Deciduous forest
Evergreen forest, high cover density
Evergreen forest, medium cover density
Range, grassland
Mixed (evergreen and deciduous, med to low density
Mixed masaic
Plantations
Evergreen, woodland and shrubland
It is immediately evident that this table provides a basis for estimating the impacts of
deforestation. For instance, deciduous forest on Soil Class B has a CN2 value of 66, whereas
if converted to agriculture (AGRF) it would have a CN2 value of 73, signalling a 73/66 or
10.6% increase in CN2 value.
The CN2 values finally adopted in the SWAT calibration of the upstream sub-basins were
based on the above values as a starting point, but were modified to reflect the realities of the
basin in order to achieve the best possible match with known outflows. Table 2 overleaf
Another factor is the leaf index, which would need to be changed also. The choice for these parameters is limited and
straightforward and is not discussed further here.
1
Careful examination of the SWAT manual reveals that the values quoted above are for lands with a slope less than or
equal to 10%. Higher CN values would be experienced with steeper slopes. As will be seen in this note, some CN values
“observed” from the calibration are indeed higher than the “standard” ones quoted in Table 1. However, as made clear
in this note, the main consideration in using Table 1 is to generate relative changes, rather than absolute, and the relative
changes on steeper slopes would not be so different as to markedly affect the overall results.
2
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Mekong River Commission Water Utilisation Project Component A:
Development of Basin Modelling Package and Knowledge Base
Annex E: Estimation of Conversion Factors for Curve Numbers as a consequence of Deforestation
illustrates the range of “observed” CN2 values that were determined for the SWAT subbasins.
Table 2: Observed Curve Numbers
Soil
Parameter
Group
A
B
C
D
1
2
3
4
5
6
7
8
9
10
11
AGRF
AGRL
CMCL
DECD
EHCD
EMLD
GRAS
MEDM
MXMS
PLAN
WSEV
Number
-
-
-
1
-
-
-
-
-
-
-
Average
-
-
-
45.0
-
-
-
-
-
-
-
Maximum
-
-
-
45.0
-
-
-
-
-
-
-
Minimum
-
-
-
45.0
-
Number
-
26
-
13
6
7
1
3
1
4
27
Average
-
62.3
-
66.9
56.7
67.8
60.5
66.0
72.0
62.2
65.1
Maximum
-
72.0
-
77.0
65.0
69.0
60.5
66.0
72.0
66.0
75.0
Minimum
-
50.0
-
65.0
55.0
60.5
60.5
66.0
72.0
50.8
48.0
Number
-
16
2
1
-
-
-
-
-
-
-
Average
-
73.3
75.0
77.0
-
-
-
-
-
-
-
Maximum
-
79.0
75.0
77.0
-
-
-
-
-
-
-
Minimum
-
67.0
75.0
77.0
-
-
-
-
-
-
-
Number
-
2
-
-
-
1
-
-
-
-
1
Average
-
79.0
-
-
-
84.7
-
-
-
-
88.7
Maximum
-
79.0
-
-
-
84.7
-
-
-
-
88.7
Minimum
-
79.0
-
-
-
84.7
-
-
-
-
88.7
-
-
-
-
-
-
Nb Frequency refers to the number of SWAT catchments in which the Soil Group-Crop Management class occurs
The evident range of “observed” values of CN2 for each soil group/land cover combination
reflects the breadth of assumptions implicit in assigning a single dominant land use to each
sub-basin and the level of accuracy of the many other parameters that are used in the
calibration calculations (eg uncertainties of rainfall patterns). The fact that adoption of these
values of CN2 has led to a reasonably calibrated model signifies nevertheless that the CN2
values as computed are an adequate reflection of not only the dominant land class, but also
of other land classes present in smaller proportions.
The thesis upon which the estimation of deforested CN2 values is built is that the change in
CN2 value of the dominant land class should be a reflection of the relationships between
“standard” values (as in Table 1) applied to “observed” values (as in Table 2), with a
measure of constraining to avoid unrealistic answers arising (as described below).
2
Methodology
The calculations were performed in a spreadsheet (CN Numbers 031205.xls3) with a linear
optimisation function add-in to obtain best fit. The approach adopted was to generate first
The spreadsheet is on the WUP-A accessible share drive under dBase1/Basin Modelling/swat_data, and a licensed
copy of the What’s Best! Linear optimisation add-in is held by BDP’s Dr Robyn Johnston
3
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Mekong River Commission Water Utilisation Project Component A:
Development of Basin Modelling Package and Knowledge Base
Annex E: Estimation of Conversion Factors for Curve Numbers as a consequence of Deforestation
the conversion factors between land classes for different soil groups using the ratios between
the “standard” values given in Table 1, and then to apply variable adjustment factors to these
to obtain a revised set of conversion factors that provided best fit with the observed data
(given later in Table 3).
The solutions were constrained to keep results within reasonable limits. Broadly, the
constraints used are a reflection that (i) “observed” values are an indication of the actual mix
of land classes present, (ii) the extent by which runoff will be modified with deforestation in
any particular SWAT sub-area is not necessarily the same as for the conversion of a single
class, (iii) the predicted future CN2 values will reflect a new mix of land use classes, and that
(iv) the CN2 value of the converted land should be not too distant from what is expected for
the future dominant class.
The specific manner in which these constraints was applied to obtain best fit was as follows:
(i)
Where there are no observed values, no adjustment of the “standard” conversion
factor was allowed;
(ii)
Computed values of maximum and minimum predicted post-conversion CN2 values
were limited to being within a stipulated percentage of the observed range of
values for that future land class, or of the standard CN2 value if no observed
values were available; the percentage applied was manually reduced to the
minimum feasible range (typically not more than 25%); the range of predicted
CN2 values was also limited to stipulated upper and lower bounds (eg could never
exceed CN2=95);
(iii)
Computed values of average predicted post-conversion CN2 values were limited to
being within a different and smaller stipulated percentage of the observed average
values for that future land class, or of the standard CN2 value if no observed
values were available; the percentage applied was manually reduced to the
minimum feasible range (typically 3-5%);
(iv)
The difference between the “standard” and “adjusted” conversion factors was
minimised using the linear programming add-in to give best fit within the above
constraints.
The range of adjustments or “dampening factors” determined through the above process
generally fall in the 5-10% range. However, in a few cases, more substantial adjustments
were found necessary in those cases where the “observed” CN2 value is some distance from
the “standard” value. In one instance, it was considered appropriate to override the
533569879
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Mekong River Commission Water Utilisation Project Component A:
Development of Basin Modelling Package and Knowledge Base
Annex E: Estimation of Conversion Factors for Curve Numbers as a consequence of Deforestation
optimisation to avoid an answer that led to a reduced curve number for deforested land
(again a situation where there is evidently a mix of land classes that is more difficult to
characterise as a single dominant class).
3
Results
The adjusted conversion factors between land classes are given overleaf in Table 3 for each
hydrologic soil group, based on the methodology described above.
The utility of these tables is that given a sub-basin with a stipulated dominant land class and
soil group, the effect of changing land use to another dominant land class can be estimated
by applying the relevant conversion factor to the CN2 value of the “observed” original value
to predict the CN2 value of the converted land (thus allowing the SWAT model set-up to be
adjusted and re-run).
4
Application
The conversion factors in Table 3 provide the means to estimate the impacts of land use
change in the SWAT sub-basins. Application of the conversion factors to the “observed”
CN2 values will generate revised CN2 values reflecting a complete change from one
dominant land class to another.
It can be further assumed that partial changes in land use can be determined by adopting a
CN2 value somewhere between the two. The conversion factors vary between 1 and 2.48
and, for the inverse, between 1 and 0.4, with values for the most frequently occurring Soil
Group B being between 1 and 1.64 and 1 and 0.67. Under these circumstances, it is
reasonable to assume that the impacts of partial changes can be represented linearly.
For example, if 100% change results in an adjustment factor of 1.50, then a 50% change
would be represented by a conversion factor of 1.25 (from CN250% = (CN2100%-1)*50%+1).
Table 4 overleaf illustrates the impact of 50% and 100% deforestation on the partly and fully
afforested sub-basins in terms of adjusted CN2 values.
Table 3: Conversion Factors to adjust CN2 values for transition of Land Use Classes
according to Soil Group (top is initial class, side is future class)
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Mekong River Commission Water Utilisation Project Component A:
Development of Basin Modelling Package and Knowledge Base
Annex E: Estimation of Conversion Factors for Curve Numbers as a consequence of Deforestation
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Mekong River Commission Water Utilisation Project Component A:
Development of Basin Modelling Package and Knowledge Base
Annex E: Estimation of Conversion Factors for Curve Numbers as a consequence of Deforestation
Table 4: Revised CN2 values for partly and fully afforested LMB sub-basins
533569879
Subbasin
Hydrologic
Soil Group
CN2
Existing Mgt
Landuse
101
201
203
204
205
207
209
210
212
214
301
305
306
402
405
406
411
412
413
420
421
423
424
426
427
431
510
513
514
515
601
602
603
604
605
606
607
608
610
611
612
613
614
615
616
617
618
619
621
901
902
903
904
906
910
911
912
913
915
916
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
D
B
B
B
B
B
B
B
B
B
C
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
D
A
B
B
55
75
61
61
61
70
61
70
70
61
67
67
67
67
67
55
66
48
55
68.4
60
55
88.7
67
61
66
68
66
68.4
70
66
66
77
71
66
55
69
61.6
65.6
66
66
66
67
60.5
69
69
69
69
69
60.5
66
66
66
77
66
66
84.7
45
65
65
EHCD
WSEV
WSEV
WSEV
WSEV
WSEV
WSEV
MEDM
WSEV
WSEV
WSEV
WSEV
WSEV
WSEV
WSEV
EHCD
MEDM
WSEV
EHCD
WSEV
WSEV
EHCD
WSEV
WSEV
WSEV
MEDM
WSEV
MEDM
WSEV
MEDM
DECD
DECD
DECD
DECD
DECD
EHCD
EMLD
WSEV
WSEV
DECD
DECD
DECD
WSEV
EMLD
EMLD
EMLD
EMLD
EMLD
EMLD
EMLD
DECD
DECD
DECD
DECD
MEDM
DECD
EMLD
DECD
EHCD
DECD
50% Conversion to AGRF
CN2 rev
Factor
1.16
1.03
1.03
1.03
1.03
1.03
1.03
1.07
1.03
1.03
1.03
1.03
1.03
1.03
1.03
1.16
1.07
1.03
1.16
1.03
1.03
1.16
1.00
1.03
1.03
1.07
1.03
1.07
1.03
1.07
1.03
1.03
1.06
1.03
1.03
1.16
1.04
1.03
1.03
1.03
1.03
1.03
1.03
1.04
1.04
1.04
1.04
1.04
1.04
1.04
1.03
1.03
1.03
1.03
1.07
1.03
1.02
1.17
1.16
1.03
64.0
77.2
62.8
62.8
62.8
72.0
62.8
74.9
72.0
62.8
68.9
68.9
68.9
68.9
68.9
64.0
70.6
49.4
64.0
70.4
61.7
64.0
88.5
68.9
62.8
70.6
70.0
70.6
70.4
74.9
67.9
67.9
81.4
73.1
67.9
64.0
71.7
63.4
67.5
67.9
67.9
67.9
68.9
62.8
71.7
71.7
71.7
71.7
71.7
62.8
67.9
67.9
67.9
79.2
70.6
67.9
86.4
52.6
75.6
66.9
100% Conversion to AGRF
CN2 rev
Factor
1.33
1.06
1.06
1.06
1.06
1.06
1.06
1.14
1.06
1.06
1.06
1.06
1.06
1.06
1.06
1.33
1.14
1.06
1.33
1.06
1.06
1.33
0.99
1.06
1.06
1.14
1.06
1.14
1.06
1.14
1.06
1.06
1.12
1.06
1.06
1.33
1.08
1.06
1.06
1.06
1.06
1.06
1.06
1.08
1.08
1.08
1.08
1.08
1.08
1.08
1.06
1.06
1.06
1.06
1.14
1.06
1.04
1.34
1.33
1.06
73.0
79.4
64.5
64.5
64.5
74.1
64.5
79.7
74.1
64.5
70.9
70.9
70.9
70.9
70.9
73.0
75.2
50.8
73.0
72.4
63.5
73.0
88.2
70.9
64.5
75.2
71.9
75.2
72.4
79.7
69.8
69.8
85.9
75.1
69.8
73.0
74.3
65.2
69.4
69.8
69.8
69.8
70.9
65.2
74.3
74.3
74.3
74.3
74.3
65.2
69.8
69.8
69.8
81.5
75.2
69.8
88.2
60.1
86.2
68.8
E-7