Impacts of spatial variability in urban hydrological modelling: a case study of the Canal do Mangue Basin in Rio de Janeiro, Brazil

Sampaio Júnior, James de Melo; Reis, Marcelo de Miranda; Paz, Igor da Silva Rocha

doi:10.1590/2318-0331.302520240004

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Scientific/Technical Article • RBRH 30 • 2025 • https://doi.org/10.1590/2318-0331.302520240004 linkcopy

Impacts of spatial variability in urban hydrological modelling: a case study of the Canal do Mangue Basin in Rio de Janeiro, Brazil

Impactos da variabilidade espacial na modelagem hidrológica urbana: um estudo de caso da Bacia do Canal do Mangue no Rio de Janeiro, Brasil

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

This study analyzes spatial and rainfall variability of an urban basin using the Stormwater Management Model (SWMM), a semi-distributed and open-source hydrological tool. The Canal do Mangue Basin (CMB) in the city of Rio de Janeiro, Brazil, was modelled with three map resolutions, varying the numbers of sub-basins, and three rainfall spatialization methods: arithmetic mean, Thiessen polygons, and Inverse Distance Weighted (IDW). Simulated water levels were compared to observed data at control points, considering different rain gauge densities. Results showed good agreement between observed and simulated volumes. The arithmetic mean method performed best overall, with errors ranging from 0.00% to 18.60%, while IDW showed higher accuracy for specific nodes (10.82% to 15.18%). The study concludes that spatial resolution, interpolation methods, and rain gauge density significantly affect model performance, providing valuable insights for optimizing hydrological modeling in urban basins.

Keywords:
Urban hydrological modelling; Spatial variability; Rain gauge; Land use and land cover; SWMM

Hydrological Classes	Forest Area > 70%	Forest Area < 70%
A	25	45
B	55	66
C	70	77
Urban	92	92

Property	Map R1	Map R2	Map R3
Sub-basin Area (ha)	0.83 to 168.29	7.61 to 231.81	61.39 to 394.89
Sub-basin Width (m)	50.61 to 1369.33	198.83 to 1854.62	515.19 to 1745.68
Sub-basin Slope (%)	0.24 to 59.09	0.50 to 48.21	0.68 to 48.14
Average Sub-basin Slope (%)	15.09	18.40	19.25
Impervious Area (%)	0.00 to 100.00	0.88 to 99.80	0.88 to 98.37
Watercourse Roughness	0.015 to 0.070	0.015 to 0.070	0.015 to 0.070
Average Watercourse Slope (%)	2.80	2.80	2.80
Curve Number (CN)	25 to 92	25 to 92	25 to 92

Hydrological Classes	Lower Limit	Upper Limit
A	25	72
B	55	81
C	70	88
Urban	51	92

Event	Spatialization Method	Resolution 1	Resolution 2	Resolution 3
Event 1	Arithmetic Mean	R1-1-M	R2-1-M	R3-1-M
	Thiessen Polygons	R1-1-T	R2-1-T	R3-1-T
	IDW	R1-1-I	R2-1-I	R3-1-I
Event 2	Arithmetic Mean	R1-2-M	R2-2-M	R3-2-M
	Thiessen Polygons	R1-2-T	R2-2-T	R3-2-T
	IDW	R1-2-I	R2-2-I	R3-2-I
Event 3	Arithmetic Mean	R1-3-M	R2-3-M	R3-3-M
	Thiessen Polygons	R1-3-T	R2-3-T	R3-3-T
	IDW	R1-3-I	R2-3-I	R3-3-I
Event 4	Arithmetic Mean	R1-4-M	R2-4-M	R3-4-M
	Thiessen Polygons	R1-4-T	R2-4-T	R3-4-T
	IDW	R1-4-I	R2-4-I	R3-4-I

Nodes		N-19	N-35	N-45	N-50
Observed Max Water Level (m)		9.00	7.90	2.30	7.10
R1-1-I (280 times)	Simulated Max (m)	9.04	7.79	2.03	6.30
	Abs. Diff. (m)	0.04	-0.11	-0.27	-0.80
	Percentage Diff. (%)	0.44%	-1.39%	-11.74%	-11.27%
R2-1-I (222 times)	Simulated Max (m)	9.03	7.78	2.10	6.27
	Abs. Diff. (m)	0.03	-0.12	-0.20	-0.83
	Percentage Diff. (%)	0.33%	-1.52%	-8.70%	-11.69%
R3-1-I (186 times.)	Simulated Max (m)	8.99	7.82	2.01	6.27
	Abs. Diff. (m)	-0.01	-0.08	-0.29	-0.83
	Percentage Diff. (%)	-0.11%	-1.01%	-12.61%	-11.69%

Node	Lower difference	Upper difference
N-19	1.25% (R3-1-M)	4.09% (R2-1-T)
N-35	0.89% (R1-1-T)	7.72% (R1-1-M)
N-45	4.35% (R2-1-T)	12.61% (R3-1-I)
N-50	9.15% (R1-1-M)	12.11% (R2-1-T)

Node	Lower difference	Upper difference
N-19	10.82% (R1-3-I and R2-3-I)	13.73% (R3-2-M)
N-35	0.00% (R3-2-T, R3-3-I and R3-4-I)	2.07% (R1-3-I and R1-4-I)
N-39	9.12% (R2-2-M and R3-2-M)	22.35% (R3-1-I)
N-40	6.20% (R1-2-M, R2-2-M and R3-2-M)	20.80% (R3-3-I)
N-42	18.60% (R1-2-M)	27.29% (R2-3-I)
N-48	15.18% (R1-3-M)	16.96% (R3-2-T, R3-3-T and R3-4-T)

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