Adequacy of methodologies for determining SCS / CN in a watershed with characteristics of the Pampa biome

Cunha, Zandra Almeida da; Beskow, Samuel; Moura, Maíra Martim de; Beskow, Tamara Leitzke Caldeira; Mello, Carlos Rogério de

doi:10.4136/ambi-agua.2715

Abstract

The Soil Conservation Service Curve Number Model is a conceptual model intended for estimating effective rainfall (ER). This model is grounded in a parameter - referred to as Curve Number (CN), which is determined from information on the characteristics of the watershed. The Standard Method (M1) for determining the CN is based on soil and land-use tables; however, some authors have proposed alternative methodologies for defining the CN value from monitored rainfall-runoff events, such as those described by Hawkins (1993)HAWKINS, R. H. Asymptotic determination of runoff curve numbers from data. Journal of Irrigation and Drainage Engineering, v. 119, p. 334-345, 1993. https://doi.org/10.1061/(ASCE)0733-9437(1993)119:2(334)
https://doi.org/10.1061/(ASCE)0733-9437(... (M2), Soulis and Valiantzas (2012)SOULIS, K. X.; VALIANTZAS, J. D. Variation of runoff curve number with rainfall in heterogeneous watersheds. The Two-CN system approach. Hydrology and Earth System Sciences, v. 16, n. 3, p. 1001-1015, 2012. (M3), and Soulis and Valiantzas (2013)SOULIS, K. X.; VALIANTZAS, J. D. Identification of the SCS-CN Parameter Spatial Distribution Using Rainfall-Runoff Data in Heterogeneous Watersheds. Water Resources Management, v. 27, n. 6, p. 1737-1749, 2013. https://doi.org/10.1007/s11269-012-0082-5
https://doi.org/10.1007/s11269-012-0082-... (M4). The objective of this study was to evaluate the impact of using these methods for determination of the CN parameter on the estimation of ER, taking as reference forty rainfall-runoff events monitored between 2015 and 2018 in the Cadeia River Watershed, which has characteristics of the Pampa biome. The different methods assessed for definition of the CN parameter resulted in contrasting performances with respect to the estimation of ER for CRW, as the following findings: i) M1 gave ER values with little reliability, mainly due to the classification of antecedent moisture content classes; ii) M3 provided the best results in determining ER, followed by M2; and iii) the ER values estimated according to M4 differed from those observed, mainly for events with lower rainfall depths.

Keywords:
effective rainfall; extreme events; hydrological modeling

[1] ^*Corresponding author: Zandra Almeida da Cunha, e-mail: zandraacunha@gmail.com

Land use in the CRW	Reference*	Hydrologic soil group
Land use in the CRW	Reference*	B	C	D
Water body	Water	100	100	100
Pasture	Regular Plantations - in straight rows	75	83	87
Grassland	Permanent fields - normal	58	71	78
Forest	Forests - normal	60	70	76
Bare soil	Plowed soil - in straight rows	80	87	90

Event	R_total (mm)	I_a (mm)	R₅ (mm)	AMC	CN_obs	ER (mm)
1	14.0	3.3	31.5	I	73	1.1
2	19.0	4.4	40.8	I	64	1.3
3	113.3	15.7	49.9	II	47	24.6
4	32.0	14.7	7.3	I	63	1.8
5	33.0	17.5	0.7	I	52	0.9
6	50.7	6.2	0.0	I	36	4.0
7	65.8	19.2	61.4	II	40	5.1
8	53.1	22.2	62.2	III	55	4.0
9	64.8	6.2	80.4	III	66	17.9
10	37.3	8.5	41.1	II	76	7.5
11	36.5	0.0	10.9	I	37	2.8
12	18.4	3.2	46.8	II	81	3.0
13	13.5	11.8	0.7	I	99	0.8
14	40.6	1.2	0.8	I	28	2.2
15	42.6	18.7	34.3	I	72	4.6
16	71.5	33.4	3.1	I	28	2.1
17	33.7	24.6	58.1	III	98	6.3
18	132.7	26.7	13.4	I	43	25.5
19	18.5	12.9	22.6	I	92	1.1
20	41.7	15.2	40.1	II	65	4.3
21	24.7	12.4	17.5	I	78	1.8
22	102.9	11.1	33.8	I	49	23.7
23	44.6	19.2	1.7	I	62	3.6
24	101.6	27.2	21.7	I	40	12.0
25	30.1	4.9	39.3	II	69	4.6
26	23.2	18.2	4.5	I	95	1.5
27	29.2	20.4	41.2	II	69	0.6
28	32.1	13.5	69.6	III	57	1.6
29	26.8	15.1	36.5	II	91	3.9
30	47.3	24.2	17.4	I	42	1.4
31	32.7	9.4	47.3	II	72	4.5
32	97.4	37.6	0.7	I	47	10.3
33	26.1	6.2	7.4	I	68	2.8
34	54.6	6.3	30.7	I	60	10.8
35	59.0	9.7	7.8	I	66	13.7
36	42.5	7.3	0.2	I	41	3.1
37	53.1	16.9	0.7	I	44	3.7
38	65.6	20.7	1.9	I	65	11.2
39	37.8	14.2	25.0	I	91	11.3
40	40.5	10.6	39.1	III	84	11.6

Soil classes	HSG*	Land use classes	CN (M1)	CN (M3)	CN (M4)	Area (km²)	Area of the watershed (%)
Yellow Argisol	C	Water body	100	87	28	0.05	0.04
		Bare soil	87	87	92	19.4	16.0
		Pasture	83	87	92	11.7	9.6
		Grassland	71	87	92	31.2	25.8
		Forest	70	25	21	33.7	27.9
Grayish Brown Argisol	D	Water body	100	87	28	0.003	0.003
		Bare soil	90	87	92	1.7	1.4
		Pasture	87	87	92	0.8	0.7
		Grassland	78	87	92	3.1	2.6
		Forest	76	87	26	1.9	1.6
Red Argisol	B	Water body	100	87	28	0.01	0.01
		Bare soil	80	87	92	3.4	2.8
		Pasture	75	87	13	2.2	1.8
		Forest	60	25	6	6.2	5.1
		Grassland	58	25	18	5.6	4.6

	Observed	M1	M2	M3	M4
Minimum	0.6	0.0	1.0	0.2	0.6
Average	6.5	6.5	6.5	6.3	3.7
Median	3.9	0.8	3.7	4.2	3.1
Maximum	25.5	49.9	34.1	27.1	10.9
Re (%)	-	-100.0 to 582.9	-68.3 to 380.8	-77.0 to 431.9	-73.2 to 261.4
NS	-	-0.8	0.6	0.7	0.3
P_bias (%)	-	-0.4	0.0	2.3	41.9

Brasil

Brasil

Adequacy of methodologies for determining SCS / CN in a watershed with characteristics of the Pampa biome

Adequação de metodologias para determinação de SCS / CN em uma bacia hidrográfica com características do bioma Pampa

Abstract